{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "# Training a Multi-Turn Agent for Mathematical Reasoning with End-to-End Reinforcement Learning in AReaL\n",
    "\n",
    "This notebook utilizes components provided by AReaL to quickly set up a multi-turn agent for mathematical reasoning and train the agent through end-to-end reinforcement learning.\n",
    "\n",
    "This agent solves mathematical problems, e.g. GSM8K, through step-by-step reasoning.\n",
    "\n",
    "The following code blocks primarily include the following steps:\n",
    "\n",
    "1. **Experiment Preparation:** Load experiment configuration from YAML, configure environment variables, start the SGLang server, and load the GSM8K dataset.\n",
    "\n",
    "2. **Define a Simple Single-Turn Generation Workflow.**\n",
    "\n",
    "3. **Modify the Single-Turn Workflow into a Multi-Turn Workflow**, allowing different numbers of rounds per data instance.\n",
    "\n",
    "4. **Generate a Group of Multi-Turn Trajectories Each Time** (i.e., GRPO).\n",
    "\n",
    "5. **Test the Multi-Turn Workflow.**\n",
    "\n",
    "6. **Integrate the Workflow into End-to-End GRPO Reinforcement Learning Training.**"
   ]
  },
  {
   "attachments": {
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66CN3d/eLFy+K/1SBNhgaGhYWFqalpYlbbgKBIDc399ChQ8rKytbW1o2NjU+fPj1w4MD8+fMLCgpMTEx+/PFHCoWCZAGDwaisrFy3bp25ubmRkZGOjk5zc3MXT1FTU6NQKGPGjMGNirKyMgzDfHx85OXlm5qafv/998bGxszMzDdv3qALVFRU8GBHQ0PDN9988/Lly+LiYj09vaNHj2IYVl5evnHjxg8//FB2krMAMFiAG8wwpcMOF0dHx19//RWSdH2xQ9BMVfGiDEww6xB7e3svL6+tW7c+fvzY2dm5oaHh5cuXjx49qq2tZbPZfn5+I0eO5PF4CgoKr1+/DgoK8vT0FH96U1NTQ0PDBx984OjoiGGYhoaGjo4OlUo1MzPr7CkIPp8vFAqRXFBXV6fRaDExMWZmZpcuXVJQUDh9+vTevXuzs7PRc9XV1TU1NaurqzEMy83NLSsrQxs1l5eXKykpbdq0SYI/MAAYakD+dNhBp9MjIiK++eYbFouFf/QkkUgnTpzYuHGjioqKtBc4WEEx1SVLlvj6+urp6WVkZNTU1KSlpV25cqWmpoZEImlra8OnZBwlJaUpU6bo6+vjPyIFBYUPPvggKCjoxYsX3t7eVlZWSkpK2trap06dYjAYpqamzc3NKSkpp06dotPpU6ZM0dbWnjFjBjIzlJWV5eXlCwsL0fkOn2Jra5uamsrhcPDqmJ6eHpfLDQkJiY+PnzRp0s6dO83Nzevr63Nzc93c3BQVFRUUFJ49e3bhwoX4+Phffvnlgw8+8PDwMDAwKCoq+v33342NjbW1tQsLC2NiYn777bdx48ZBBAQAug/03w4v0tPTV65c2dzc3KbDZXj21g4oNBoNt0MEAgH063YTNpudmJjo7u6up6eHch7Pnz8/fvx4QkIChmF2dnazZs1asmQJKql0SBdPqa6uFggE+vr6bd5RQUGhM4/qxYsX3333nYmJyaJFi+zs7FC4GM1MCw8Pp9Fourq6M2fO9PLymjZtGvwlAoDuA/pjWA/2gJypZMaHhIaG/vnnnzweDw0OgfFlvYDH48mLGNCn9AiUgYX/jwDQO0B/DCPbo00bIdgeElYh+Ex3fJo7REMAABi2gP4Y+oSFhaFBT/gZsD2kBY1GwweHCIVCVJT54osvBukGwgAAAL0G9Mewa3IB20OmoiF8Pl9OTm7x4sVLly6FaAgAAMMH0B9DFrA9ZByhUBgTEyOuQiAaAgDA8AH0x3AZaerj43P48GFVVVWpLg3oVkAVoiE9gkql/nMkprbfQTf8vy5abAAA6DugP4Z+1BRsj8GrQobwhjKRkZE0Go1KpSYnJ7e55f+jJ4TCf/5BCIVUJlNaq/1neSRS63/QEBfRv/9nwf9+6erq6uzsbGJiAgoGALoA9McQr7nASNPB3iYzxAKqkZGRUVFRKSkp2DDAxcUlMDDQ1dVV2gsBAFkE9MdQrrlA1HRQt8kgFYI2mhkCs8siIyNDQkL+v1byv/jOmIFhmLONDcXIqEcvS62sxCRIh8ujVlbSRFvGJL94QWWxqAyG+KMuLi7ff/89eCEA0AbQH0MBqLkMBxUyeAOqVCp148aN7T0P3xkznG1sXMePpxgaYkOI5OfPUwsLI+/cERcix44d8/X1leq6AEC2AP0x6IGay9BmsKuQ5OTkFStWiJ9xGTt22fTpQ092tCf5+fOQmJiUJ0/Ql0FBQcuWLQMjBAAQoD8GMVBzGeYqRPbbZCIjI8U3iXUZOzbQz8913DhsOJH8/PmmU6eoFRVIggQGBkp7RQAgE4D+GFIj1c+fP+/h4TEoPhYDQ16FtHE+/ti9e7gpDxwqi7V81y4qiwUSBABwQH8MndliERERo0aNGhpdEkA3h7gLBII+NuvOmTNn7ty5/a5gxMWHy9ix369fP+SrLe9k+a5dKXl5GIY9evQIqjAAoLB7925prwHoAXQ6ff369ZcvX+ZyufhJR0fH2NhYAoEghyYTAEMabW1tZ2fnOXPm6Orq0un0OhFpaWmJiYm1tbUkEklbW7ubfxLodPqJEycePXokEAicnJz6q7mGSqV6eXmhY98ZM8588422hka/vPKgxnX8+MS0tLqmprxnz3z9/KS9HACQMqA/BhN0On3lypU5OTnGxsaNjY3IuwoICDh69CgMNh1udKFCnj9/bm1traOj804VoqWlJScnl56eXlZWZmVlZWJi0i/+2d69e/NEH/Rdxo498803fX/BoYG2hsZcJ6fEtLS8V68oBMK4CROkvSIAkCagPwYN6enpPj4+FRUVQqFQS0uroaGBSCSeOHFixYoVMlj7B6SoQvLz82/fvv38+XMNDQ0KhdK1pCCTyQUFBXl5eampqaNHj+67BEHdtkh8XN6zpy8vNfTQ1tCob2pKef487/nzuZ6e2tra0l4RAEgN0B+Dg7CwsK+//prNZpNIpMbGxrq6OiKR+Ouvv9rb2w/egVTAQKuQmJiYsrKyrlWItra2k5PT/fv3y8rK0tLSpk+frqen15dCXnh4eEpKCoVIvPXdd334noYsLuPGRd27R62oGGtlBRYIMJyB/OmgbLKFCR9AN3tk8DYZNI+uM7Walpa2cuXK5uZmMpkcERFhaWnZOxeESqW6ubm1dnn4+QXCuK1OCImMDP7zTxdb28vXrkl7LQAgNaBXYhAEPh48eGBkZITfDwICAi5evAjiA+gQMpm8YcOGe/fubdq0CY2BEQqFNBrt448/dnd3v3jxoriQxXFyctqwYYOysjKNRlu1alVhYaFAIOjFu0dFRbUOKScSQXx0QaCvL8XQMOXJE2pRkbTXAgBSA+ovgyPwMWbMGCaTKRQKz58/D4EPoJsVmaVLl+rp6WVkZPD5fAzD6uvr//rrr6ioKDU1NRsbmzYOB+p/SU9Pr6mpuXv37rRp03pRiImKisrLy1vt4+Nibd3f39OQIr+0NK+kREdV1cXdXdprAQDpAP6HjBIWFvaf//ynqanJ0dER3RWMjY1/+eWXadOmwXgxoI9eyLZt2zw8PL7//nvxLm4MwxYvXvzFF1/0xQWJjIxs3UbO0rK/v5WhhrONDZqSIu2FAIDUgPyHLPLxxx8nJSXxeDxHR8fs7Gx0AIEPYCByIW3Gp9JoNJQ34vP5Pc2C4OGPUpEKAbrGbd06KosFs8iAYQv4H7IFnU5ftWpVUlKSkZGRk5MTEh8+Pj4XLlwA8QEMhBdy4sSJadOm4V4ImUw+dOjQ1KlTFRQUkAvy4MEDVL55J+Xl5Sj8MfDfzVDAdfz4VgskKUnaCwEA6QD5D5kLfLx69YpAIDCZTCqVKhAIAgICdu7cqaKiIu3VAUM5F5KWlnblypWamhoSiUShUJydnZuamvLz82tra9PT0+vq6lAdsOsXT0lJSUxMHGth4TttmqS+oUFMbUNDYnq6jqbmnHnzpL0WAJACoD9khZiYmHXr1jU3N6MbAIPBgLQpIHkVgsanEgiE2bNno0dramqoVGp9ff07JUhdXV1UVBTF0NB3+nQJfjeDlbqmpqh797Q1NX2XL5f2WgBACkD9RSYICwv75ptv2Gy2j4+PkpJSRkYGpE0BaVVkoqOjP/roox9++MHOzg6Po165cuX48eNt8qod06vG3WEI2g04JSODSqVKey0AIAXg3iZDaVMfH5/r169D2hSQvApZsmSJeDpVKBTGxMTExsaSSCQPD4979+6hpIhAIAgMDARDrr+gGBpSWSxprwIApAP4H7KSNhUXH7/99huID6DfiYmJefz4cXJycvs8aXsvBLdD7ty5g7ayEwqFJ0+eDAkJ6ZYLAnQ/ggpduMCwBPwPqZGenr5y5cqmpiYSieTi4nLt2jUejxcQEBAYGIjfAACgv4iJidmyZUtLSwv6kkQiycvLk0gktOGcg4ODgoICmUyePHny77//fvv27cTExLKyMjT/o6qqqjUspqDA5/NPnjxJo9GOHDkCmWgAAPoC6A9p3gzYbDbK9CHxsX///vfffx8CH8BA4OTktH79+uTk5JSUFD6fT6PRUMdsamoqPjcMBx8LhDQHOkYHqDRz7969R48eaWhotH8jKCgAANAd4FYnBcLCwoKDgzkcDhIfGRkZRkZGaHswEB/AAIEqLOvXr6fT6eXl5enp6cnJyeXl5ajNu7M5hJ1N/qiurl62bFl0dLSamtoALxwAgKEJ3O2kljYNCAi4efNmWVkZgUA4ePCgh4fHO+crAEAfkZOTI4twcXFZv349OokUCZVKpdFoVCoV1yLix2/evGGxWHV1dfiZkJAQKMH0kfKKitYUKsw/BYYloD8kB51OR5Otkfg4c+YMskCg1QWQCvjeckiRoOOuN2Sg0+mhoaF//vknj8f773//e+fOHfijCwBA7wD9ISHodPrKlSsLCwsJBMLSpUt/+uknJD5+++03cLAB2aHrDW/JZPLBgwfXr1+fmprK5/PbBKVhjgUAAN0H9IdEW10cHR1dXFyQ+PDx8Tl8+LCqqqq0VwcAPa7gLFmyRNoLAQBgcCMr+oPOYO49cIRIJDjY24r+bYcNxVYXU1PTU6dOQasLAAB4r9CDBw+SkpIsLCzGjx8/cuRI+EwCDBOkcP+jM5hZ2TkMZmvwis5gYhjmYG+bmf0kMzsHy8ZuxMVjGEYkEhZ4ec6fN5dEJGBDotUlICAgJyfn6tWrPB7v/PnzHh4eID4AAMAwrLi4OD09XVtbm0KhWFtbjxkzBoQIMBxQlIzIYIh0BoZhrSKjHUhziMNgMH8+98v1uHhxFZKZnXPmXITDJLs1/quwwdbq8uTJk9TUVNRnC60uwBAG5n/0lKVLl9rY2Ny8efPBgwdZWVlGRka4ELGwsCASiXp6eqBFgKFHP+sPOoN581bCz+d+6ZdXa6NCbsQlZGbntP6TlXM6NBgbDK0uRkZG69evP3v2bElJCfTZAgDQHhsbm7Fjx9Lp9NLS0gYRRUVFSIgYGRnp6OiYmppOmTLFxsYGhAgwlGjd02GglQcqpmAYNsneVvw8boqIvI0n+JkOPZL2r/mp/ypv0cvKGnQ6ffbs2Y2NjSQSSbzVBfpsgaFNSEhIcHDrB4PS/52mCnSGma8vhmGPHj0yMjLKz8+/d+9ecnJyfn5+TU2N+GWamprICDE1NZ00aZKNjQ2RSAQhAgx2+kd/3IiL33PgSIeyY5K9bS/CpCgXwmC2Fm4ys5+0L9Dgb3H6RLBMZUTEW102bNjw2WefNTc3Q58tMFjgcrkVFRUtLS2WlpYyrj+EQiGbw1FVVu6sZ/idF8iO/kAjyKqqqkpKSnJzc589e1Ykor0QIZPJFArFwsICqjPAYKcf9Edmds7a9UEDbU5kZufsOXBE3DLB32uBl6eMJELwVhcfHx/U6gJ9tsBgoaamJjk5uaCg4ObNm6amptu2beupBJGk/hAKhedv3bqZnHziyy9JBga9uADDMA6Xe+bGDRszsxn29kijsDmcl+Xlo8hkdYn8hW2jPxD19fWVlZUsFis/Px8JETqdXlNTw2az8Ws0NTWhOgMM9/xHG/ExcGURB3u70yeCxUs8RCKBIUq2ojNSlyA7duz4448/uFxuQEDAmzdvTp48CX22gOzD5XKLi4tviaitrWWLmDhxIolEwmQYvkBQ8fatqZGRdkd74HXnAgzDWLW1dzMzf09MPL1p00SR2Hry+rXfrl0L3NwOf/aZppQMSy0RlpaW48aN8/DwYLFYNTU1ZWVljx8/RqUZNpuNx0SQFklNTUXVGeidAQYRiv0oPj5d/fGAigASkbDGfxWRYPxzeARSHt5enpnZOVKXIOKD1c+LePz4MfTZAjJOTU3N/fv3MzMzHz58WF1dXV9fb2Fh4evr6+npqaurK+PlwkY2u5jBsB01qjOV8M4LMAyrrK5+UVrayGbHp6aOMzdXkJdnVFVhGPaaSq2srpaW/mgvRJAp4uLiQqfTy8rKsrOz8/PzGQwGckQaGhpyRSBThEKhmIlAQgRMEUBm6dOtEc98EImEXds3S2ZomHdrpsRu7YYgUTQkZ9f2zWfORWRm50hLgrRpdTl37lxKSgr02QKDxfCor69XVVVdsmTJxIkTx48fP2LECD09PUzmeVZUlPHixSpPz15f0LqpXm1to+gW/qy4uLahQUdT82V5eWsOo64OnZedRmUtLa2JIurr6z08PGg0WmFhYUFBwfPnz4uLi3EhgkwRZWVlPT09CoViYGAApggwBPXHGZEJgQTBru2bMQlCEsVO9x44gkIhn4o0h1QkCJ42JZFIv/7666JFi1Dby6+//mppaSkvLy+xlRC2h60AACAASURBVADAO+FyuS9fvrx8+XIbw8PLy0tfX19VVRX1ZwkEgg7/6AoEgvYnO7ySymJRDA2xAUMoFKbl59uMHDm6k51j33kBopTJNCcSdTQ08ktLaW/e8Pj8J4WFyBdp4XAwmURLS2uMCCcnp8rKShqN9uLFi4KCAvGYCIfDqRCBJ0VgoAgwdPQHfrOXvPhAkIiEb7dvRnGQn8MjcAlyPS6+dx03fRysvmHDhoULF6K2F+izBWTT8EhISGhubmaxWAoKCrNnz/bw8MANj4KCgvT0dCKRiLZ3wbfDFYdGo7U/KX4ll8tFB/yOlEo/UtfUlF9aOsnKSl9Hp3cXoKhpEZ1uamzs6ey89aefcgsL9bW1H+bmYoMEvDpjb2+P8qooJtK+OtPhQBHo4wUGpf6gM5go9uFgbycV8YEgEQnz583FMAxJkNaVnPunTUYCTbniaVNlZeVPPvkEWl0A2VQecXFx165dww0Pf3//efPm6enp6ejo4CGPhQsX8ng8DMPQv3uKrq5uS0sLeq5QKMwsKDAzNsYGjGI6/VlR0acLFih0YjG+84LW32Nv3mS9fDlz0qSpEyY4WFs/zM3lCwRONjYz7O2PXLyIDR7axETEqzPiTbxtIqsPHjwQ7+O1tLTU6VyrAYCs6I+1G/7JnH4rPfEhLkEys3Jw2bFo2fsM0VZ2AzcgtU3aNDExMTIyEg1ZDwwMbLMjOQBIS3bcuXPn8ePHdDodVx6rVq1asGBBhwmPwMBAmoj09HS8ziIQCPD+fPGTSGSIPyo+pkJOTm77zz8vnjp1gOqPfIHgblbWeAuL0SYmvbsArT81Ly+/tHTjihVkQ0O3CROOR0VhGPbFsmVONjYaqqpUFmvymDHYYKNNdYbFYlVWVpaXl6enp+O9M0iLFIhAm0IYGRmZmZmNHj0aIquATOsPfAiHt5enLAz+QoUYFEc9I3JB9ohyIWfCIwYiCCIe+MDTptDqAsig4VFTU1NbW6unp7dixYopU6aQSKQusqWff/45fkyn09EBUiRIZDAYDOSOlJaW8vn80tLSgoKCxsZG/FlCoRAf8zXB0nLgRn7R37x5kJOzwM1Np5PG2nde0Np5W1NzIzl56sSJtpaWCvLySzw8HuTkvKJSp9najtDWNjU2pr15gw0w5ZWVEjNF3N3dUe9MZ5HVrKws8cgqVGcACdCz+2Vmdg4+ilTq8zbaxFEXLXv/Rlw8iUjw9vK8ERd/PS6+31coHvg4fPjw2rVrCwsLYVcXQBZgsViRkZFtDI8PP/zQy8vL0NBQR0en++IYn/xBIpEcHR2R7OByuXw+PzY29sGDBxkZGeJzC+XkWscYyolA539Yv37g9MeDJ09yXr/euWpVry/AMOzxs2cPc3O/WLYMBUTMicT9a9ZUvH1rN3p0c0uLOZFIY7HQ7FRswDAxMsIkgnjvTDcjq+LVGeidAWRCf5w5F4Efy4L58T8SJDR47fqg63Hxu7ZvvhEXj7pz+yuIKl5zCQgIcHV1XbBgAaRNAdnJlsbFxbFYrNraWjk5ua5LLd1HXHbExsa2kR2KiooKCgp8Pl9XV/fNmzeKioroABtgqmprUcJU3HHp0QUFZWXn4+KM9PRmTZqEB0QmWFhMsLBovfuqqVmZmCTl5lbV1ZE7GZw6SOkssio+2ax9dQZ6ZwDp648z4a1jNtCxDG785mBvh5yPG3EJDvZ2rSWYcxEOof2gP9LT07ds2VJUVCQQCM6fP//8+XN/f39ImwIy1Uz79u1bQ0PDTz/99J2llr7LDiUlJQUFhYULF1IolL///jsjI0NNTc3FxcXW1jYkJAQbYIxHjMAw7L+HDtmPHq31r/SnslgVb98unDp14/Ll77zgTmZmzuvXvjNmWHUUEJGTkxtvYRESGVlEpw8x/fHOyWZdVGdg3DsgTf1xXWwTONkpvoizxn+VSH+0WiCZ2a2h1L5bIOnp6R999FFzczOJRDp48GB4eDiabTpsB6s3NTWVlpaOHj16GH7vstlMy2azLSwsPvroo16UWropOxQVFeXl5ZWUlOTk5BYvXrxo0aJJkyYVFhb6+/vT6XRVVdWIiAhnZ2cJiA8Mw+Y6OeWVlET+/Xf2q1dtHrp0546JkdEH773X9QVznZzS8/P/M3t2Z5u8jDE1tRs16mFuruu4cYpDva7aRXWms94ZfNw7CBGgL3T39xSqaKBjB3s7mSq+4JBEY1j3HDjSOhFk9cc/n/slK/tJH/UHlUoVCASo5rJmzRpciLi7uw/PG/DFixf37dtnYWHx3nvvWVpauru7o6ER0l7XcDQ8lJSULCwsvLy8+lJq6Vp2oCKLj48PmUxetGgRmvbB5/Pv37/v7++voKAwevToffv2OTs7Y5JCV1Nzj7//jpUrG5qb0RllJSVlRcWG5ubq+npDXV0tdfV3XvDLtm1dvAVRX3/qxIl//v33zEmTnMeOHaBvZEBHtPVLdaaysrKgoCAzM7O4uFi8OoOPe8eFCORVgV7Q3TtoZvYTfMs3h0mSmO7VOybZ26HiC73dTrm9w8fHZ/HixbGxsZ988glKng7nwIdQKNTS0po2bdrkyZM5HE50dPQ333zj5OQUEBAwderU4SnIJNlMS6PRWCxWfX29oaHhunXr+lJqeafsUFRUXLx48eTJk52cnMSHjHE4nIcPHyLx4e7ufv78eamoTyVFRT0tLfEzelpa4mfeeUEXKCoofLlsmZeLi+lATjEZFNWZqqqqmTNnslisDmMiuBDB86ogRIAB8T9aDQZCq/4gEmT376So/2Uu3qeTmZXT91KRnJzc1atX0aixYT7hIz8//+zZs0ePHrWza9WgQqGQRqNduXLlyy+//PDDDwMCAoatMpNMMy3Klnp6eva61MLj8VpaWoRCYRvZ0abCMnny5MWLF7cXFs3NzaGhoSdPnlRSUnJzc5OW+JAAykpK48zNpb0K6aMv4p0b4OF5VRAiQPfp1i8vdC9Hm80ijwGTYcSXR+ynOtGBAwcIBAJ02MrJyXG53JKSEqQ/5OTkKBTKl19+OXXq1LVr144ZM2bBggXvfBEej4fmRmhpaQ3oFjlCobChoYHH42lqaiopKWGDdnoYKrVYW1svX7586tSpvTA8xGVHWFgYPkm9swpLewQCQUtLy8qVK9PT01VVVTds2LBu3bqhKj6AXm+AB0IE6D49+/CEIiCyGf7AwUeA9ONrdvZLebihoqKiqqrK4/EiIiLevHmzYsUKdXV1NpudlpbG5/NHiPoOEDQa7e7duxiGzZo1C//pVVVVnT9/Pjo6mkajaWho/P777/b29vhT2Gx2QUGBgYEBkUgU1yVCofDNmzfFxcWampqjR4/uUEmw2ezGxsYRI0agOyKHw7l161Z4eHhOTqti/uabbwICAvCLBQJBTk5ORkYGmUyeMWOG7Hg27Q0PHo+Hl1rIZLKhoaFW9yoIKKWBKiwdyg7Uw9JhhaXDl3r9+vWOHTsyMjLwtGl/fMfDHQqZTKXRysvLKV3ukzcoNsADIQIMiP5A4Q+EZLZ265dGGNFqbaW9liEImUy+c+fO2bNnjx8/js7Y2tqGhoa6uroiuZCQkHD48GFHR8eqqqqbN2/+8MMPZDK5uLg4MDCwrq7O399/+vTphoaGGmLjKYuKir7++uuMjAwkWXbu3Gkucr9rampOnz7966+/IsuETCZ//vnny5cvV1ZWrq2tPXLkyEcffaSiovL1118zGIzjx49PnjyZzWYfPHgwKipq2bJl6HXE36ipqenkyZNxcXHu7u5XrlzJzc3dtGmTdN2RzgwPS0vLXpRacNmRmpp67dq1tLQ0JDsUFRVVVVUVFBTwHhYnJ6fuvKB44EPyaVNAZmmTV+2+EIGuGQAxNAODuEPTX/UXQBwlJaV169a9ffs2Ojr6k08+8ff3NzIywm/hL168CA4ODgoKWrhwIZPJDAwMrKysxD9eUygUFxcXy/+dz83lcn///Xdzc/Pjx49zudyTJ08ePHjw0KFDWlpax44di46O3rRp03/+85/WsZWPH4eEhDQ0NKxZs0YgEFCpVCaTef36dW1tbUVFxVu3btna/qM4dXV17e3tJ06cKJ7XEQqFV69effjw4ZkzZ0aNGnXv3r2IiIimpiZp7bzVoeGhpKQ0bty4npZa3ik7fHx8umN1tHlNDoczTAIfgMSECLTvAj3yP1pNbAd72/4tagwoqFVH2qsYmjQ3N+vr6x86dGjs2LGnTp0yMTFB4gB9Vr5y5QqTyUxNTaXT6dnZ2fr6+haisZLm5uYnT5784Ycf/Pz85s+f/9lnn+EqpK6u7sWLF2vXrkW3xm9ExMbGfvjhhwKB4OOPP161ahUK38ycOXPEiBE7duyYNWuWvr4+n88/ceKEmZnZsWPHsrKyLl68iMTEli1bTE1Nd+/effHixc8//3zq1KlIhdBotKioKDabHRsbq6SkdOvWLT8/P21tbdkxPGbNmtXTUgvKdrSXHWpqat2vsLSHzWY/fvz41KlTqOYCgQ+gv4SIePuupaWlnZ2di4sLjHgfhnRLf6Ab+SDyEvBpJX2f/wG0p6qqCsMwVVXVTz75ZPTo0Xv27GGxWKj5pbq6Oj8/PzQ0lE6nP3z40M3NzdvbG3cXKBTK999/HxgYePbsWT8/v1mzZgUFBZFIpNra2qqqqmfPnrm6uioqKurr648bN47BYHC5XPRG4snfuro6dH9Fz1JRUQkICNDX16dQKHJycmw2W0dHR11d/ZNPPlmxYkV0dPS+ffsMDAyCgoJcXV2Li4v19PR27dqVmJhYXl6+cePGadOmSfKe2pnhYW1tjcZ46OrqdrPU0j5SisKkGhoaPa2wtKe5uXnr1q2xsbE9qrlATKrHiA2WHfJCpH3XTG5u7osXLzIyMu7evWttbQ0BkeGGYve9hEFkJ+CBlX7pvwVwNDQ0dHR0ysrK0JdycnLTp083MTHZvXv34cOHt23bhu7lVCp1xYoVy5cvF38uj8dLSkoaO3asqanp3r17P/3009OnT3/++echISG1tbVsNvvq1auvXr1as2ZNU1NTUlLSggULNDU1zc3Nb9y44ebmZmFhwWazb9269euvvwYFBZmbmz979qyqqmr79u2jRo3CMGzEiBE8Hq+ystLY2DgvL6+lpcXOzm7lypXLli2LjIzctm3bV199pa+vX15erqSktGnTJqkbHhiGGRoa+vr6dn+MR4eRUlx29KLC0hkff/xxZmamqqrq0qVL9+/f31OJJmuTtWQWCpFI/Xe34SEvRPCuGXEhwuFwykVkZWWhgMj48eNdXV3Hjh0rraooIFv6A439YDBbt0YcFOD71NCZg0YzDQo0NDSMjIzGjBkjftLS0nLPnj0nT55sbm42NDT08/Pbv39/XV3dwoULeTxeenr633//vWDBgilTply5cmXv3r0ffPDBuHHjWvf/NDFJSEh48eKFoaGhqanp9u3bz5496+npqauru3LlyhUrVsjJyS1ZsqSkpMTf37+mpkZXV3fOnDlhYWE2NjZycnKWlpZbtmyZPXs2WoaRkdH06dNLSkomTJiQnp5+5MiRZcuWvffee4qKigYGBvr6+pmZmUFBQY6Ojps3bw4MDLS1taXT6Y8ePcrPz9+4caOpqamEDY/uZ0t5ItpkO5Ds0NTU7HWFpQtqamqWL1/eFwcFADrrmsGFiPhAMzwgkpOT8/Dhw4kTJzo5OYEdMrT5Z7/srlm7PigzOweNNicSCdeiLmGyjaPbDHQwKFY7xBAIBI8fP/7xxx/T0tIwDHNzc5s7d663t7e+vn5VVdXly5cjIyPRRhIWFhbvv//+hx9+mJeXd/z48R9//FFPT4/L5fa9G4XD4dy9e/e333579OgRyqLOmTNnw4YNpqamTU1NFy9eDA8Pp9Fourq6M2fO9PLymjZtWv+OlevM8FBSUrKysupmthSXHTExMekicNmBDyftcEqYtIiMjETGUmlkpLTXMjhYfvBgSnb2sWPHfH19sWFGfX19cXFxYWHhkydPUlJS8IAIQlNTk0wm4/0yDg4OYIcM3/oLlv3PQf/uaz8Q7DlwBPUJ4y4IIEnk5eWniuDxeKjbE39IX19/nYgunt4vrbDKysrzRLR/CEVDVq9ezefzB2JgPIvFiouLKywsfPjwYRvDo5vZUiQ7eDxebGxsG9mBux0yJTuA3iMQYMN7oNmYMWMmT548c+bMNgGRNv0yDg4OYIcM1/qLKHnKYFagQgwm2yDZsWb1qsz1ObK/2iFM9+/uI0aMUFNT43A4mKSQk5PrX/GBb0sbFxdXVVXFZrPr6+uRnMKbabvOlraRHVevXhUKhYNLdqAhWhD+6AFDNH/afZSVlU1E4AGRZ8+eJScno7oMHlMtKip6/PgxSofMmjXL2toaVMgQoFu/gieJpnhlZuU4TGo1FSTfVEJnMG/eSiASjL29PLvT+eIg2oVOUqsD+oqGhkZzczOKjmKDii7qLN00PDqTHSoqKvjQDhmXHUCvMdHXT5H2GmQtIGJnZzd16tTc3Ny0tLT2dkhOTk5aWtr48eOhKDNs6i+EVv+DzmSu+VeISLKpJDM7Z+36IPzLriXIjbgE0TVz8T1rJLJGoE/o6OhQKJTExMSxY8cOlk12OqyzIOVhYWHxzmbaDmUH3mzs5OSEsp/Q0QoMzx3vrKysXF1dkR1y9+7dgoIClA6pqqpKTk5++vQpFGWGUf0FxSlQOUPCTSVIUuDHHUqKPQeOZGbnkAgEVHzp9/1fgAFFVVV14cKFd+7c4XK5Mq4/uqiz4IZHF820nckOfEOW/fv3D3bZAfUXoH/tEEdHx2fPnrVplsGLMlZWVlOnTnV2dgYVMujobgkcVV4yRZUX0YHkIqjic1c7nIF2JjwCXYDkERIoaASIzO7/wuVy3759W1tbm5GR0djYWF9fv2jRIktLS2y44iICk3nZkZCQwGaz8TpLm5aWzgyPd8qOPo4LkylS8vKkvQRg6KCvrz9lypQJEya4uLgUFhYmJyenpaWJF2WKi4vz8vISExOnTZvm4eEBKmQI6o9/IiDZOZ/6r8rMzjlzLsIhVEL6Y5K93aerP0bpk+7Ufby95qIgCHouJhtwudyKigoqlfpUxOvXr9ENqaGhgc/na2lpGRgYDGf9MbjiHXidxdPTc+7cuWpqah0mPPBxYaiBVlx24D20Q0Z2iENlscAF6Q7lLBbaFkDaCxk0zTITJ06cO3eueFGGw+EUinj16tX9+/dBhQxF/0N0I8fbSSRZgiERCWv8V3WhPObPm3v934HrVqNHOdjb4eEPfCM6WRAcXC63paWlUURzczN+D3N3d7e3t4c9RWVNdty/fz83N/f58+fi8Q40tHTRokUTJ04cP358F3WW9nuyIOWhoqIyVFOlJiYm6KC8shL0R7eQl5f2CgYTysrKliLEizLZ2dmoU6ZMBFIh0CYzKOhBCyIKVeAlmBtx8TKS7iQRCadPBH+9defLV6/f91uKYdjP4RG4ESL5kkpycnJxcXFaWlp7wYFrjsmTJxsYGMydO1dVVVVXV1ddXV1NTU2SqwXeKTtqa2vb/4/Dh5Z2+L+Mx+MhwwMfjo7Oi9dZ1q1bN6jjHd2BWlmJiUbcAl1DFfkfQF+KMpmZmffv32+jQlCbzLx588ALGSL6Y43/KpH+aB2Emrk+5+fwCBnRH6J95nJevnqNiyQGg0kUZWYl43AUFRU1Njbm5uYWFBTweLy6ujrxWKKxsbGlpeWoUaPU1NQmTJgwevRoVVVVLS0tJSWlbm6tDsiC7EBisUPDQzzeERsbm5GRMUzqLJ2Rmp/vO+OfGcRAF1AZDGkvYdAXZczNzR0cHNqoENQmQ6PR0tPTIZ06FPSHeBeMrFkgqEdm1/bNdAYTzT/dtX3zgL5jfn7+1q1bGxsbW1pa2Gw2n89vbGzkcrkGBgYWFhbiakNJSUlFRQVthg4+x+CSHd3pZ2lpaWkT78ANDxcXl0WLFg29OktnUCgUColEpdPLKwbNXlFShFpbK+0lDE0VgrfJlJWVMZnMvLy8jIyMqVOnurq6DroJQ0Obno2ARENFfw6PQClUGbFAEu78hbfdokkhEpg/xuFwysrK0E70CKFQKC8v//btW64IEomko6Ojp6dHoVDMzMwGdDFA/8oOd3d3FO/oTj9LmzrL8DQ8cFzd3CIjI1Py8iCC+k7K/93uBLJf/atCnj59+vfff6enp9fU1KB0akVFBRpotnDhQjs7OzBCBqX+IBL+sUDwDVaQBUJnMAcu6Ulv3Xq31XHp8NHM7Jwdu/Yhw+NMeERmdg6RSDgdGowNMObm5hs2bDhy5Ah+65KTa93Mj8PhVFdXNzQ0vHz5Mjk5WV1dXUVFRVtb28jIyNjY2MTExMrKikKhQKtLhwgEgtTU1IsXLyoqKgYFBfXjnrRtOlnayA6UKvXy8rK0tERttJ05VWB4dGcEO4Zhyc+eQQmma1ILCtCBq6urtNcy1FTIhAkTxCsyqFOXRqMVFBS4ublBNHVQ6g8SkeDtNVckOxLQQdiZ8IHeFJfBbC2pONjbeXvNbaNC8NGoVqNHtcZOz/0igcoLQktLy8PDIycnJysrq6ysTPwhgUDQIqKhoQEZJPLy8koiVFRUcEVCJpNHjRqloaEBigTR0NBw6tSp8+fPu7i4zJ07t+/hGC6XW15eXlBQ8PLlSzS3o00nS5tUqb6+PormtH8p1Enb3vCQl5dXVlYezoZHG/CP8hABeQdkMlXURYgrNmCAKjK3bt168uQJmheSkZGBmgPaRFOpVOoff/yRkZFRXV09efLkgIAAEokk7e9j6NP6kb1HT6AzmGs3BDEYTDSTA3khA73NPdr/5bqoq3aBl+cke1vkvuBz2fGBp6dDgyU2GI3L5bJYrMbGxsrKyoSEhNjY2FpRQVdehPhNrj3ovqWmpiYvL6+urq6pqUkikdTV1W1sbIxEDDdFQqPRduzYUVJSsnPnTg8Pj75sDideYcnLy2tqamKz2fjcDjwUTCaTkdDpLFUq3tKSnJx87dq12NjYNoaHqanp2rVrfXx8hq3h0R43V1cqnY5h2KOwMCjBdIqtrZmVFdIfjx49kvZqhiz19fUFBQWPHj0SH+KOYZipqamzs/Py5csdHBwSExP37t2rpaX13nvvCYXCuLi40aNHHzp0SF9fX9rLH+L0WH/grgORSNi1fTNSAN7zPXdta3UdBroQg1RIm11t8ZLQru2bpZJH4fF4FRUVGRkZN27cSExMRLUYBQUFMplsZ2dnbGxcUFBQXl5eVFTU2SvIy8sriNDQ0EBOCa5IbG1tzc3NlZSUhrAiefPmzdatW9ls9t69e83NzXutOTIyMlgsFrI62ldYkNXh4uJiaWnp6uqKXKguXBa81CLe0iI+wwMMjw4JCQkJDm4tgAb5+QX6+kp7OTIJmRwSGYl+SseOHfOFn9IAU1VVVVBQEB8f/+DBAzQ7FcMwTU3NL774YsmSJYcPH3779u13331nKJLLz58/DwgIOHbs2OTJk6W98CFOb/QH2m/lRlw8iUigi6QA0iJnzrXGL65GXRrQqV90BjMrOyfx7t/JKWlCDMM/dUpLfCCEQmFzc3NFRUVWVlZ8fHxiYqKcnJyKioqenp6Tk9Pq1as1NDTq6uoqKyuZTCYqQ3ZfkaipqcnJyeGKZIhVbZqamg4ePPj06dPvv/9+1KjWOlpPyyvFxcUo1dHQ0ICmsIhf1iZSqq2t3VmRBSEQCDgcTvtSC9qnBpVahsMMj75bIBRDw8t79oAF0hYVFczW1s3NjUqlgvkhScrKylJSUhITE1E0FcOwdevWrV27lsFg0On0GTNmIBezqKgInV+8eLG0lzzE6aXLvUbU//Km6u0/W8Nk5Xzx1WYOh9Ph/iz9DoNZkZyS1qqeZEN8IMNDXV195MiRxsbGkyZN8vT0RCqkoqIiKSmptWy0YMHs2bM5HA4aStbU1NTS0tKFIhGI4HK5uGEoLy//+vVrBQWFhw8foqpNm2TrILVJHj58GBcXFxISMnLkyNraWnV1dSUlpXf6HDU1NY8fP2YwGOgn2SbV0b6BtjtD3lDIo7S09NSpU+KlFjzksX///uGcLe0+vsuXBwcHU1msqHv3wAJpi7k5VUTrDwp+OBLE1NRUT09vzJgxSUlJCQkJBf/mf9FGd/hlDAajrq5ucP0WHV7+B4ZhFy5e/vHkaSKR8NOJ4IXL3kcnkSGhrKw8Z/ZMEpEwyd6WSCD0lx2C6i8oZIqDrBeJZT565IU8fPgwPDy8pKREVVUV6ZJ58+a999574ld2X5F0iHiyFdkkg0uUNDU1ffvtt3w+39XV9dSpU0VFRbq6ut7e3l999RUqvrYfY49yZDwer0PNQaFQxowZY2Vlhc+W7bCBtg18Pp/D4UDIox9Z7uubktb6IQFSIP8DmYyRyWB+SJeqqqqcnJyYmJjx48e///77Ojo6bWrBxsbG27ZtU1dXl+oyhz691x9nwiN+PveLeAq1M5A4cJhkN3/e3N5pkQ6VBxIfp08ES3GTly4QCoWNjY0vXry4cePG/fv3kQqhUCgLFy784IMPRowY0dmzulYkTCaTxWK1KTF0U5To6emh6KWxsTFKuaKDzhYjAaqrq7/88stnz54RCIS1a9eOGjWqpKQkIiLC2tr6q6++Sk9PDw4O7nCMffsw6YQJEyZOnDhu3Djkc3SzfQZXHqdOnUpPT2/fT7tu3ToIefQOtylTqKLqFUiQf7CwwAwM8HzMH3/8AZ230oLD4bx+/VpOTm7kyJG4LYpS8IqKiocOHTIwMJD2Goc+vdcfC5e9jw9CRY0nERcuobKIaFKIMYlIRDvVtY+LOkyy66Y1gnacQb0tSHDg2+B5e3lKptW2L/B4vOrq6tLS0piYmLi4uNraWgMDAxcXlwULFogbIV3QRpFwOJzGxkbUd/P06dOioiIUg+jaJsEDJUiaqKioIIGiLALda3F1MmLECCUlJSMjI3QGrglBaQAAIABJREFU/7JfZArKZyBXo6GhQUdH54cffqisrAwNDcXDH6mpqZs3b/7++++fP3++c+fODl9HPNVhY2OjoqKiqanZo/GyXSuPpUuXQry0j1Cp1OV+fkiCHFu3bri3444Zg2lr4+IDYqeyAJ/Pl5OTkxftApiVlbVt2zYTE5N9+/YRCLL4mXboodj7mWAiEYCLDwd7OyKBsOjfQgyDWUEiEr/dvplEJKCR7TfiEpAWycz+H7+kQznS3vBofX0iAQkRIpGwwMuzix1xZQdFRUVDQ0M9PT0ikejs7BwfH5+cnHz79u3c3Nw7d+74+vq+M2KN3At0f0UlCaFQyOPx+Hy+m5tbc3OzUChsY5N0KEpQoATDMDSYpAt1oqSkhA4UFRXl5OQUFRXxAAS68YtbC0ig4MdaWlri3gyaxoZkBzoQCAQ8Hk8oFHK5XD09vY8++mj06NEKCgriFii6UigU8vn8Dn0OfBud3m3dB8pDMlAolGPff79p0yYqlbopLKx10Nb48cPRCFFRac181NVtXLMmJSWltTMoKAjEhyygoKAgFAqrq6uvXbv2008/OTs779ixA9puZd3/QMUXdCw+cmPt+iCkLRQUFNDNw8Hebs3qVfgFaJhpVvaTzKyc9taIzRjrpYsX1Nc35OQ+xTDs1etCNQ31WdM8Jtnb4qM+Pl398aBQHh2GQiorK3Nzc5EKYbPZVlZWH374Yb/8JhK3SdqLEhaLVVlZWVFR0Z3yTdcgpSL+JZ6uQGKFy+WKrwp9iTRTm5cikUhffvnl5MmTN27caGNj88UXXxgaGmZkZBw+fNjR0XHdunWPHj26efMm0hz4Tjo99Tnaj4YD5SFJqFTqxo0b0X0XGSHDS4WIAh+bNm2KjIxEJ6DsIjvw+fyzZ88ePHgQP0Mmk8eOHTtt2rSZM2cSiURkjQCypT9Q8aX9vC9xXeLq4lRSWoYuQ9NLJ9nbtS+4ZGbnIDnSWYhkmrvb/aRHshk17YsKuX79empqqq+vb2clhv4VJWhXGo6I5ubm6urqxsbGwsLCpqYm5Je8ffuWw+H0UZ30CKQ/VqxYkZeXd+zYsbt372IYpqGh8d///vfzzz9XU1NrbGxsaGhAQ2P7vm8fh8MpLi7esWMH5DwkT0hISGRkJGr6oBgbUwwNA5ctMzEyGspCxMAgMjU1KjYW114uLi6XL1+W9rKA/4fH4wUHB4eGhv7nP//x9vaWl5evrKxMT0//66+/aDTakiVLgoKCdERIe6VDk97PH+uw65XOYOIlmNOhwUQCoc3EMLzagsc4MrOfoAJNm3fx9vJE5z9d/fH1uPjBUnDpvgqprq6ura3V1dWV/KBfvILT3NwsEAiQX8LlcpFeQRM/q6uruVwuk8msrq7m8XiVlZW4LmkzY4PD4aBmevRQfX29eEUGFWvalGlGjBiB9geeOHGihYUFciZYLBaVSjU1NTUwMOjfThM0SSwsLOzkyZPiXbUqKiqgPCRGcnLylStXkpOTkQpBuEycaGJoSBE53mQDA4qRUfsnUisru37lDp+FYZhJJ+c7pPxd79I1+CJTi4owVdXkjAzxb9PX13fp0qVge8ggPB6PzWZraGiI/87h8XgsFktVVTU3N5fJZLq4uMAeorIyfx0pjM7in45uM9oXSjKzc86ci2hfcBHH28vTwd52kr2dePKDSCTEXL4gbvgDEhMoaAAJl8tFB3gBBa+qiF8snjJpU5FBB/hUD1SyUVBQUFNTw2MlAwQquFy5cqX9JDEzM7N9+/bB1qOSJyQkBKkQ8Tv0kMTFxcXExCQwMBA2eRmkxMTEREZG2trarlixAiRIv6PYi81f0HFnrSt4R0xmVg6uP1ptj1A78WoL3syCNIf4q63xX4VbJru2bwbxIXlwuaCiooLJNjdv3vzll1/s7e2R0dLY2PjXX3/5+Pj4+/vz+fwOCy6qqqowSUyKBIpAjkhqaipSIeXl5fgFXesSmVItFBGtXouJCX7S2dnZ1dUVNMfQgMlkoiA/SBAp64+9B47gBsb8eXM7vKZ1HKpIf9BFuzu2fdTerjWR2mUlZc+/7/Lp6o8HddoDGGjYbPajR49oNFpdXd2LFy/QSTTqvqWl5aSI9iHT/fv3g/KQBVxFSOWt24gYcfXTNbjOAHkxfGAwGDExMSBBpKk/zoS3bu+CjonETkd3zJ83t/2gsJ7uLIOOUUwEADqjqamJSqUGBAR88MEHQqEQzUVVVlbW0NA4deqUuPhQVVV1dXWFqAfQoXoAMQF0CJFINDQ0LCwsRBJEXV3dz8/P2NhY2usaInS3uYjOYCJVgQwJUufjWUhEAj4lrOu5qF2LD/y9ZBA6g4k23gOkC41Ge/36tbW1NaoZaWlp6enpaWhoYBhWUlKCrlFUVNTQ0Dh8+PD58+dBfAAA0H3GjBkzZ84c5HkwGIw///zz/v37+J5cgIT0B4p9tBZEJv0zTL2Li3F10kXatD034uKR+ECxVslsZdcLzoRHLFr2/t4DR6S9EADLzc01MTEhEAjl5eV/iUCzy3BUVVXd3d1v374Nu7cAANBTdHV158+fj5ddysrKLl++/PDhQ5Agkqu/nAmPYDCYRCJhjf8q1N7SdWXE22sucj4YzIpuroPOYO4R3dFPhwZnZT9p3TBWqvvZdtOhAaQIm81+/vx5SkqKm5sb+qRSXl7u5uaG9m5AWwQfOHAAcqYAAPQaAoGwZMkSNDiutLQ0Nzf3zJkzGIZNnTpVVVVV2qsb6v4HXnnZtX0zKjoQiYSuKyOT/n0U9bl0B2QneHt5EgkE9Had5VtlRHx07QABEkBVVXX58uV79uz5448/cnNzExISYmJiKisrL1++zOfzR48eDbYHAAD9JUGQ4OBwOFlZWQkJCeL9/MBA+R83byXgfSvo7ttF+ANBEgmUzOzWCevdT7ai8aZnwiO6zrdKC3A+ZBBbEfiX1tbWCxYsyMzMbGpq8vf3l+rSAAAYahKkoqICFV+SkpIMDAygHWZg/Q/c/PhWlMlA9ZTufPRH13Qngirur2AYdl10j5e14gueTUE6DHpzZISmpibxbWV4PF5zc7O2tvaAzjQDAGAYMnHixDVr1iAXBLXD3L59u7a2VtrrGrr6A5kfn67+GLkRqJ7SnVtv92/P6C1QTQdtq4uCJpjMkJmdg7IpRCLhdGgwUlRE2KBZ2jQ1Ne3fv3/dunVlZWVoDPyFCxfOnz/v5ubW981iAAAAxFFWVp40aZKnpyfafJvBYFy6dOmvv/6CLOpA6Y82UYxu1lPEb89nzrXWU7oAGR6figTHzVsJQhmLVrSOfBVtdtMqPk4E4223slYeGm7weDw6ne7p6fnq1St3d3czM7PRo0cHBwcHBQV5eXlJe3UAAAxBlJWV3d3dFy9ejAbGvH79+sKFC9AO02u6sqnxtCl+r8U3s33n63YzAoIbHt5enol3/vr53C9yGJaWnpmZnSMjwz/wPttd2zeTiAQ8niLtdQ1r+Hz+H3/8oaSk5Ofnd+vWrfz8/Ly8PBMTE1tbW9ipEgCAgYNAIHh7e3M4HLwdJiEhwdzc3NLSUtpLG1r+B6qM4FEMXI5086XXrF7Voylk0Vevo4PKStaeA0dkYcDX2vVBaPGnQ4PF9dA7E7jAwCEQCO7fv79jxw4021RVVdXe3v6DDz7w8PAA8QEAgITbYZKSklJSUsAC6Wf90aZ7liFyMrp/6+1OQiJLdHdHt3arUaP+/73ENrqTFvi8+V3bN+PiA1WLZKpCNNwoLi5evXp1T/dtBgAAGAgJwmAwoqOjoQrTz/oDlU7w8AcaC9b9Wy8qwXQdAcEntWMYdunPKPHzjH8nkkkFvCvH28vTW8wBQkslEmD+v3Rgs9lbtmwB8QEAgHSZOHGip6cnCoKgKgxMBBmo+eu9A5VguoiAII+EzvxnOxVDI0Px/WVuxMWjvIXkQe6Lg70d6goWd4Ag/yEteDzeli1b0tPTkf6AJlsAAKSbRV26dKmZmRlUYfpff6DP+nj4tPvNt23kRRcRELRZHYPBRDrDZ8F8NGiEzmQi1+F6XHxPN7HrO2vXB6FU7OnQYPHzyAGS5Y3xhjACgeCPP/6IjY1F4kNZWdnDwwNmmwIAICNVmFu3bqWnp4MEkRX/gyRqbOm6BIPu5fhoURKR8Onqj5FkQQcSrsKIxz7aPIQUGJgfkkcgELx69Wrnzp248xEYGGhoaCjtdQEAMKwhEAjz5s1zdHRUVVXNzs6Oi4uDKsyA6I/ezd1Ck8Qys3M6szEcxAwVZK7MnzcXmSJ0BtPB3o7x7wQOCXAjLh7FPlp3+m1ncqBvAZpfJE9xcbGnp6dAIGj9Iysv7+7uvm7dOjA/AACQOnZ2dl5eXhQKpaGh4e+//4YqzAD6Hz2du4WnUG/EtXbztqd1z7l/XxOJG5JoIxh0v/f2atUimdk5EgiC4HvwOtjbtR/AivcDQ/OLhOHz+eKZU3Nz8/DwcBAfAADIAlpaWjNnznR2doYqTH/qDyQL0H23p8M/2qdQW2eRdTLSA3ca8ICng70dKr78HB5x+kRrCOPnc78MqARpnXMqypy2j32IT0MBJE9SUhKeOVVWVj506JC8/MDWDQEAAHoXBIEqTPfp7u9xXBn0ArRnGx4y7aIEgxKviPnz5uLPwremGzgJsvfAEfTu7WMfbYCd5yQJh8PZvn27eOzDyclJ2osCAADouB0XqjADoD9QL0xvow/IArnRSTMLXoLJ/LfBBFVhUC/Mjbh4BrMC2SEDJEHwzGmHsQ8EyoVA84skEQgEP/74I/5Jws3NDWIfAADIbDsuXoVJS0sDC6Qf/Y+KvkQfUD0Fw7DOBqujm3obdYIHQfBM6EBIkMzsHPT6HcY+EPiaoflFkpSUlISFheGVl4MHD4L4AABA9qswqampYIH0SX8gTYBGpPcdvKtl7Yag9hLE26t1yirqefnf855IuPyzTS4KhfRfFuR/trftKPbRPpjSL+8LvBM+n3/8+HEkPuTl5QMDA8lksrQXBQAA8O4qDFgg/el/0Ps8d5wk2r8e39uljdXhYG+HrIX2Mc81/qtw5wNJEOSILFz2ft/3qBPf3raLy/DJYz1t/wF6TVJSEj5tzNTU9PPPPwfzAwCAwVKFAQukj/6HLZ7J+Gffk77dfdFsMfRqew4caeNhfCqqfSCR0ZkEQYWSq1GXcCulL0YInkcR32GuayB8KvnYqby8vJ+fH4gPAABkHwKB4OTkhCyQW7duPX/+XNorGsz9t+I9KX1njf+qq1GX0Mu28TBQCrV9CQZ/Iu58rN0Q9KmYIlm47P1ezGjHp32I7zD3zq2Aof4i+dipubk5mB8AAAwWXFxckAWSnZ19+/btiorW9CTQh/qLKADR0+GnHUIiEpCBgddicA9jARrW3omlgbQLaspFOdbTocH/GCHre2yEoFwL8d+Ia7dmv0LxRSKUlZWJx05h4AcAAINuKPu4ceOgF7dP+VM0exTfd76/0g8oC4LXYnAPA2VUb8TFdxbsQE256Ik34uL3HDiCd9agF+m+Cvmno6cbfsb/Tz4F80MiREZGisdOYeAHAACDCzs7u/fee8/Y2LioqOjhw4cQRO0Q+R5ZBVj/QSISkJ+Bah+4h2Fjbd31sFH8iaj+ciMu/npcvLeXJ/JFelqO6Y6iwptfIHwqATgcDm5+QOwUAIDBiJaW1owZM1xcXOTl5dPT03NycsAC6bH+QJ/4kVUwEKAJH6iMgiyNJ0+fYhj207lfuu5twVUIkh2tlgmTSSQS8HJMZ4NG2kc63gne/ALhUwmA99xiGAaxUwAABikWFhbu7u4UCoVGo6WkpIAF0gv9YYv3pAzcvq8O9nbXoi6hJpSqqrcYhslh2Ld7D77Txmit44QGnw4NRioE/YMeuhEX33V3zL+Jlh50FEP9ZaARCAQxMTF48gPMDwAABnsvrry8fFJSEqRAeqw/BqIFpjO8vTxPhwZfjbpkNXoUhmFPcp+uXR+EIh1dOxkO9nanQ4N3bd/cpkKEl2NudNTT29OOYhAfEqCkpIROp6PjL7/8EsQHAACDFwKBMG3aNEtLSxhH1iGKWJegCGq/DP/oJiQi4eihfQuXvS8npiF+PvcLkUj41H9VF42y3l6ek+ztsrJzbsQliBsnqFnm9t17c96bpa2p0djYpKCo0P15pnQG80rstb7Mnge6iUAgEB94unjxYtAfAAAMaiaLKCwsROPIyGSyqqqqtBc1SPQHKrtIxv/4/3ckEkgi0TNz+jR1dTXkXiAZ8XN4hGg3XdsOhQiJSDDQn3Xh0p/ycnKCfzMEiMcpqcmpaZhQTignxP59SE1dreuV0BnMr7furKp6SxTFTfr1uwTaUlZWdvXqVaQ/Ro4cSSKRpL0iAACAPqGvr79w4UIajfbw4cO0tDQXFxdLS0tpL0pWUNi9e3fXVzCYFchOmO4xVWI1CC1NzftJj4pLSo8e2ve+3zJtLS20hoaGhpevXt9PenTjVsLLV4VaWpriPSkRFy6t++Kruto6ZWVlgpGRsrISny/g8/noUT09vQkTx01ycJw4fqKConxlZaWF2cilPgu7WEbQ11vz8l8oKSvdibs68N/0sEYgEJw9ezYtLQ2ZH99++62NjQ34HwAADHYMDAwaGhry8/PLy8vJZLKVlZWi4rs/+Q8H3v1TkErTh7eX58/hEQwGMys7x9vLc43/qvnz5t68lYDmryM75AYj/kZcPJFIcLC3mzjh/9j7Evimqm39kyZN0zYd05amSVvaUqATBQq0BRRHKggiCILD1fvUqyKoIIhXn/5RvA4oMjj2Knj1qk8QECcmFRyhBUrp3NK5TdKkQzpmHv+/lR2Ood07gDK06f7e+3Frc87JSXr23t9e61vfSnl/6386OjvDROG33jovc/LE8alJldV1ladrk8bEP7f2pabmpq6uLm9v/p2L5kslkY+vfoZhmClTMtzcwz+WPlZcWsYwzFsbX7tcn3v4wtVzLCYmZt68eZR8UFBQeAD4fP6UKVMKCgoOHjxIQyAX5v/Bdoa7zEDlNt/tOzjQ9sP1flDx7cvr3+jo7IyJidn1fx/dvmBOY5N87/c/FZVWZE+ekDQ6cdfnHz3zzzWJiaNn5cwcFR8r8PFhbBAUmT41i/TuH3z4cVEJVAK/99ZGqjy9DNi1axft9kJBQeGRiI+PnzRpUlhYWHFxMfUCuTD/sSuyACO9J3JfZX+JWEjuW1Dt0v+u7ExzU/Md996/a/dXE8cl1zc2B/j7iSMj0Iv+woBb591iZzjyFrhaYVGxm8/13b4DKNDyyEMPTJo44dJ+Toqzy26p5xgFBYVHhkAyMjLUanVRUVFHR8eVvqNBgfPKQiGNxcnCosupwZw4IR3JRL/8+puRMTHIA411gm9RwQ92h1OIK1C9zI7dX02fmpUYP/Lwr0evu3rqb0dP8Hhet8+/+Zejx4+fLC4pq3BURuGdP06eKkJ96VKTk/7nnrsux0cd9mhubmbLbmnwg4KCwlPtyMrLy48fP45iIYJhXwhzXvwDmXShUMTl9CBHq9DHn0C/3IHgenF5fO+01NSU1FSrSf/p/+1gX+rp7t6770DhqaLZN93ULG+JCBPNvP5qhmFmTJ3yw0+/7dj1JcMwErF44DVbHN6pEC/x8/vPB+9euo9GQWr4QoMfFBQUngc+nz9p0qT09PQffvihoKAgIyNDKpUywxsX1lbUTVuWiw7Xot+MCePnzL5pzuybHrz/77fOne3n58eBCltrTs6NY5KSp07JeHzZw0ga0u8KX33zbV5ePseLi5a0ru7enj5NWGgIwzBpaSn93rFFqXpw2eMMw3h7e//8w97L9UGHO6xWq6vy9ErfDgUFBcUlgUQiyc7OjoiIKC0tbWhouNK3M1TiH2diHt/uO3DZUjBzZt/EOon9v/99CsVd9h/84f1tH3lxuEJ//3+tfVamao8cEVHXKPPx4aeMHT1xUsbjfkK1uuPT/9uOLqJ2oLGxwWAwTJ866diJooTYmB+//55hmNjo/txz3UvrW1vbOF5eR3+GAyguD/Ly8qjylIKCYviEQH755ZeqqqrJkycP8xTMhVUho2ITNyaklwiFp4qixDd9/Onn7/17K4fjlTF50j13LVYoVPEjoydPTG9pbcs7XtjQqDCYDHNnzwwKDJh/y5yPPttx4vgJVSsEUTo7O2XNTXs61LHRUSMiRIjT9CvqeXj5Svg9h7P59Zcv86cbzrDZbHl5eehnqjyloKAYDiGQ4uLisrIyhUIxzAtxz4t/uNaJvP/hxxMnjL8MKpAWpcrVRv2Ztf86fPgnm91+z11L/nbXHZ/v/jY4KGDyRPAmiRoRkTQ64fBv+TFRUSaTmWEYs9UyatSoSRMmqDraezrVp09X+/n7+/n6dXT25B8/OfBDffDhx+i9nlz56NSszEv90ShYKBQKNvly2223UfJBQUHh8SGQxMREasd+AfoPNlqgVKoujwpknaMIBeG9rf85dPin0LCwb3ZvX770wZLyqjGJ8ZER4ft//LlXo+lQd56ubZiWOVEo9C0oKq2uaywoLE1JGj0759qsSRNiRsbNu2VexIiIGVdlpiaN/vXIUYchnWhgte3CBfNuv23+ZfhoFCyamprY5EtmZiblHxQUFJ4NiUQyadIkm81GO9KdL/9A0QL077f7DrhvSPsXgYpQUEAiY8J4Lw54pcfGRC9b+nD56drCktKe3t4ZU6dcMz0rPEx04Mdfvv/591EjYyekpVw9dYqfr+CHn36TiCPTU8YyDJM8JlESGdnQLA8PDYVfpo6NjAiHnkATJ/artpVKop5ateLSfSgKLFyTL5MnT77St0NBQUFxacHn8ydOnDh69GgUAhnOXmTnyz9QwiVj4viMCeOVStW6l9ZfIgry3b4DDz8K5EMsjsx9exPU2fK4DGNva++4eea13d29R4+dSklK9PKCO09LGmO1Wvp6NSiEZbFYe3p7R4SHd/f2Vtc1MgzT2tbR2d2dnJTQJG9paJLp9PqCk0BrYqIlrtW2vgLBni8+uxQfh8INbDYbTb5QUFAMNyQmJo4ZM6arq2uYh0DOV3+KusC8v+2j3Lc3tbwEyoy9+w/ePCvnIgpBIA/i6PmCwh65b286earo5Kkif6G/2WyeMmmiWt3lzeNFhItOFpV78/hRkRG/55+QRImnZ0UfPV6o1+sVqtYREeGZGeMbm+Xlp2ua5S3dPb0jo6MmTRjX0CTLO3GKz/Nuam5CjiYtStW8hXfAV8Dj/Xpo/8X6FBTnj+bmZvQDTb5QUFAMHwQEBKSlpUml0mGuAjlf/oG6wCgd9qO5b216+NGV72/76GRhEVsZ++dw8lQROJaeoR3ojf5x/70ZE8afPFUEwQk7o9Pqpkye8tCD/8g/eUoqFU8cl1JZXZd/opDL8xb6+06dPJHH410/Y+rubw4EBwXMumEGdG+PkdoZ+48//c4X+IyMhTrbuNjo44XFtY1NrJzFqS/hcPJ++eFP3z/FRen5Eh0dTZMvFBQUwwdZWVnHjx/fvXv3cO5Ix33++efP89AAofCX345U19YhKzD4uaZ2+xe7larWgAChg9PBv+fEd/sOfP7F7l9+O7LxzXe2O37QaDTI8OOJx5c9eP/fo8SR3+078OTTz8HRXkxiwqglixaeLC7je3tfP2MqwzDhotCa2gaFqnVMYoJEDN6sp4orfAR8by5P3dUVLRFbLNayitM2qzXA37+ruyc8THSqpMJut/v7+Rw5CoIDpbLVUW3L7Pj0PyHBwX/pK6T4U7DZbGvWrOnt7WUYJicnZ+bMmTT+QUFBMUwgFAr7+vqqqqqUSmVsbGx8fDyPd2F2GB6AC/jAc2bfhAIVKPPyza7PX3hp/clTRd/tO/DdvgModIGaxrm6titVrahpC+rYgr3snNk5Yke3W6VK9Xbu+9/tO6hWd3rzvK1WS0xM9P99/MHhX496gwqEaZTJR0ZLK07X2Bhm9g0zisurenv7goKEbR3qW2bdwDD2r/f9ePCn38JCQrQ6/XUzpvn4+BwrOLX72wP+fn6zb7zm8E8/ozdF4taVjz0SP3LkxfgaKf5Sz5eR9K9AQUExzJCenp6YmHjo0KGioqLMzMxhaMfOQQHw8wQINh9dqVSq2CxJi4OOnCwsalGpkCL1nHtYUWio0Wzicrk+fH5bWzv2GEdjOc7YpKQnHn3Ey4vTKFPMmJbZ2d1TVFIREODX1d139dTJkRHhre3qH376XafXLbr15pCgQHTujj3f9Wm0c3Kuj4wIYximpOr0sWMng0NCbpwx7fcjR1G1C/ifxsTs+vzj8//sFBcXGzdufPPNN+12u5eXV11dHRIUU1BQUAwTmEym3Nzcbdu2xcXFrVq16qqrrmKGGS5s0o8SR67936fE4kgkznh4+UqlSnXzrJw5s3OUShXnPMgHeKJ3dmr6ND3dPSTyAeyDYfwEgjdeXVdUVnn0eOHV2VOCgwLjY6MTR40sr6oLCPBHZbQCPp/H4wr9haVlVejUyuo6X4FvcFDgicJis9nc2KyoqKi5+cbrxBHhP/2WX1FV4/wgUeIwUegFfXaKS1d5e6XvhYKCguJyg8/np6WljRw5sqampqqqahgW4l5Y/IPFBx9+/O2+A2w+RSQK7evT8H346D+5XC6Py7VYrSGBQYjlMQxjNJl8/XzV6k69Xj/wguPHpY2MjZ48KeNkUfGXe77hMByBr4/Vauf7eNttdpvNZrFaOXYbx4trs9kc6gGrzQZbZ7sDIB2A/4GoieM/HYEYjkNRYHf85AX/Z7aabVabVCqWy5WoxOavfXsUfxI2my0hIQH9KZ988slly5ZR8QcFBcVwg1qt3rJly44dO2bMmPH444+npPTviurZ+JOCl3/cd+/Ns3KUKtUH2z5mhR2IZ7iip7vnrP/u/ONH1EQmY0K6WBzpaoWeOXnS3r0HfHx8OF4cs9ns6+NjdxAaxm7n8by9vfkMx8YwXj7ePK63DwhJ8GwpAAAgAElEQVR2bBaOl5fFYuH7eDM2eM1iMvb09lrtTHjYCINR19fXY7fZrRaL1Wrz9fOzWq2zc3KQ4SnFYKi8vfXWWyn5oKCgGIYQiUQTJ048cuRIgQMJCQnDqhD3zwtuo8SRUeLIjLfHs2W0SG2KZCKuh7FaVIePyDl6xwQFBf7+0/n6uzsjHwMwedq1DMPkvvkG9r0++JDKPq4wvvzySxR4i4mJiYqKutK3Q0FBQXElVaj79+8vLCycPn36sCrEvTgFPxDAmMBcfvyVfXO//rcUV6TnLQ1+UFBQDGdIJJLk5OS8vLxh6EXmgUUHbPTlMjTppfgTUCgUBQUFKP7B5zs1QxQUFBTDWYWqVCqHmx27B/IPiiHU83bp0qU0/kFBQTGcMW7cuPT0dIFAUFxcXFRUNHwKYTyQfyhVEP+g6ZVBi/z8fPQDrbyloKCgEDlUqFKpVKFQFBUVdXR0MMMDHsg/Ck8VX+lboCDCZrPt2bOH9ryloKCg6KdCNZlMpaWlDQ0NzPCAB/IPhCiHoTvFYINMJmNt12nPWwoKCgrmjAo1ODh4WHmReaz+lOZfBieOHTvGij9oz1sKCgoKxkWFqtFoTpw4UVdXxwwDeCD/QE4ktPhlcEIul6MfqPiDgoKCYqAKFXmRDYcQiAfyjxaH/vScoATlyjp/UPEHBQUFBQuRSJSUlBQWFqZWqwsLC4dDIa7Hxj9Yx1WKwen8QcUfFBQUFK4YM2ZMXFwcwzDDpBDXy1PNx6j+Y5A7f1DxBwUFBYUrEhMTx4wZIxAIhkkhrqfxD4rBjOPHj6MfqPiDgoKCoh8CAgLS0tKkUukwKcT18kjzMWdLGgJc2+NRXE5Q8QcFBQWFG2RlZWVmZgoEguFQiOtx/OO8uQUViFxm2Gw2Kv6goKCgcIPIyMi0tLSwsDCNRlNWVubZKlSP4x+qVir+GJxobm5GP1DxBwUFBQUJsbGxYrEYuSXl5+d7cAjE0/gHAjU/HYT48ssvUfCDij8oKCgoSBgzZkxycrJAIFAqlaWlpVgVqlwuP3nyZGsr7LeHLjyNf5wsLKLxj0Eu/rj11ltp8oWCgoLCfTs6hmGqqqqwKtTDhw+vX7/+l19+GdLREU/jHwjUW2wwiz/4fP6Vvh0KCgqKwYvExEQUJ8aqUHU6XU1NzbFjx5qbmy0WCzNk4Wn84+QpiH9QDGbxx9KlS2n8g4KCgoKEmJiY+Ph4gUCAbQdjcoBhmI6Oju7ubmbIwtP4BwKtbRls+Prrr1HwIzo6+krfCwUFBcXQMAJhGMZNOxiNRqPT6ZghC69haH56/jW6FBcLZrMZ/UArbykoKCjO3wjETTsYvV5P9R9DyXyMBdWoXjbYbLY9e/bQ+AcFBQXFhRqBMOR2MD09PRqNhhmy8Cj+QTE4IZPJWlpakPiDxj8oKCgo+kGtVu/Zs+fnn392JRlsOzpSO5ju7u6+vj5myILHeF7n23MFNowO5Q7FZcOxY8dQ8EMqlVLnMQoKCop+aG5u/uabb3Q6XW9v74wZM4KCgth2dCdOnDAYDLW1tUqlEilCWJhMJja1PRTB8zzz03Oaj5WVVzAM879rXxwZEyMWR2ZMSGdZizgyktbuXrril+joaBr8oKCgoOiH4ODgkJCQgoKC//znP2az+YYbbggKCmJVqLW1tadPn66oqEhLSxMIBH5+fgKBgBn68Cj+gXDO+EeUOLJFqVKrO9XqTuYU892+A9grzJ190z/uu/dS3umwE39MnTr1St8OBQUFxaCDRCK5/fbbVSrViRMnPv30U4ZhEAVBRiC1tbVIhTp9+vSEhAQ+n+/t7e0B+lOe59W/nDOA8f/+96lffj0y4+ppKF9z8lSxUqlyNQ5Bv6dtci+6+IM6n1JQUFAMBJ/Pnzhx4sKFCzs6OsrKylgKgoxAjh49ajAYUDsYiUQiEAh8fX0FAkF3d/eQ1p96ov7jXOYfGRPGOwtkJsA/c2bfxLKNQgcLQYxkzuycy3Pbw0T8ER0dHRUVdaVvh4KCgmIwgs/nz5gxQ61Wf/LJJ4iC+Pn5XXvttVOmTMnLyysvL0ftYGbMmCGVSvl8Po/H02g0yIhsiMKj+EeLo/72zxXWoqhJlPgmlpFQXBQ0NTWhH2jlCwUFBYUbiESiuXPnms3m7du3l5WVffTRR97e3mlpaZMmTaqrqzMYDKgdjFQqRRKQIR388LT6WxT/8PLiXukboXDCZrO9++67KP4xcuTIK307FBQUFIMakZGRs2bNmj9/vlgsLiws/OCDDxoaGpKSkpARCNsOJjg4ODAwkGEYgwPM0IRH8Q8U+XjwkceodGOQgLZ9oaCgoLggSCSS2bNnsxQkNze3t7cXGYGw7WC8vb15PEhfmEymoduCzqP4B2t7Om/hHQOrWiguP3bt2oWCH6iXIwUFBQWFe/D5/Li4OJaC5OfnFxQUeHl5oZpb1A5GKBQij5AhDY/iH/+4715W/PHCS+spBRk8lbeLFi2iwQ8KCgqKP0FBTp48qVAofH19kVNqYWGh0WgMCQlhhjg8in9EiSNz39rkSkE++PDjK31Twxe08paCgoLir1CQhQsXLlmyRCgUKhQKs9nM5YK6sbi4+PTp02hrp9PpqP5jsCBKHPnNrs/ZApb3t31EKciVwqlTp3x9fXk8XlxcHK28paCgoLgg8Pn86OjoBQsWLFmyJCIiQq/Xo98rFAqZTIac141G49AtweU+//zzjMfhmqunR4kjq2vrNBrNyVNFHA7nfDriUlxcjB07dsqUKW1tbU8//XS/tgUUFBQUFOcDoVAYHR3N5XKbm5u7uroYhrFarT4+Pkajsbu7Ozk5ecqUKQEBAcwQhGfyD4ZhRieOmnHV9F9+O8JSEHFkZECA8Erf1/CCRCK59dZbJRLJlb4RCgoKiiFPQeRyeU9PDyqEMRgMJpOJ8o9BioAA4R23L1SqWqtrak+eKtJotKMTR1EKQkFBQUExFCmIyWRqbGzUarUmk8nmQEJCQkZGxhDVonoy/+iXiyk8VfTLb0dmXDWdUhAKCgoKiqEFoVAolUrlcnlNTY3dAZvNFh8fP3nyZJFIxAxBeJr+FIs5s29a+79PicWRSqVq3sI7XFvNUVBQUFBQDAnExMTMnDkzMTERqUCsViszlDEs+AeyJmNLcz/YRitiKCgoKCiGHjIzM6+99tqYmBihEAL5bW1tarWaGZoYLvzD1R2Exj8oKCgoKIYiRCLRwoULn3zyyauuusrPz0+lUg1d/sFBHibDCi1KFep2S0FBQUFBMeRgMpmqqqp+/PFHX1/fWbNmDdHunsORf1D8acjlcvSDTCbr9xsEhULxF98CW6zrah8SHR2N/T0FBQXFsEJHRweXyx2ixS+Ufwx3IPaQl5fXjzqg3yOSIXeAGdxwJSLszyxTkUqlEokE/T46OpqylksEnU7X1NSUmJiIOnMOaeh0urq6uqSkJA/4LBQUgxOUfww7yOXyXbt2IdqRn5/PDD8g/pGdnX3bbbdlZ2df6dvxHGzduvXFF1+Mj4+/8cYbExISrrrqKrFYfKX6/lRWVu7du3f58uWoa+iF4tixY2vXrn333Xfj4+OxB2zfvj0oKGjWrFl/+U4pKIYpKLUfXrRj586d/YIZUqk0e+xYJiTENSrgmgSRBgczcjkTFMSIxf3SH07IZEx3NzN6NOPjg3ljq5WpqGB8fZlRo/B31t7OKJWMVMqEhrpmdv5AQwNjsTCOkrN+nwj+R69nVComIIAJC8Nfv63t2IkTMq02//hx1xN3OiB1IDs7e8WKFfjTKc4Pdrs9ICBgxowZkyZNMplMX3755Zo1a6ZMmbJs2bLp06df/iiCVqv98ccfFyxYQCIQ/dDT0+Pj48OSFaVSGRERERwcTDq+ra2tpKTk2muvdeU3DQ0NOp0uOTmZdlukoDgnKP8YLsxj06ZN6D/RciuVSjMzM2H3X17OGI3MhAkMdsbU6YA9SKVMUhL+6m1tDJfLTJrEhIdjXrXbmeJiRiJhxo3Dn97by7S0MKmpTEwMe3tnHVBTw/D5THo6g13ATCa4flYWsB8sZDJGqVx0551MSAibbFIoFCwPQ9ml/Pz8nTt3Llq0iLKQP43KysqtW7e+/vrr48dDryW73a5QKHbv3v3444/ffffdy5Yt8/PzYwYrjEbj66+/HhISsmLFCtRitKOjIzU1NSgo6IIusm3btsOHD2/cuDErK+tS3i/FMIL8Eqe/r2A+mvIPD8fmzZtdmUf/JbaqijEYgBxgyYfBwJw+zXh7E8mHTsc0NTEREXjywTBAbux2oBdYmM1MdTUTEsKSj/5obnZGVrDkw2ZjysoYf38i+Whrg8hKTAy8xZlhtmjRIoZhVqxYAbTs3//OO3kyv7wcDfJNmzZRFvKnweFwzGZzY2Mj4h8cDkcqlT7++OPTp09/+OGHx44dO3fu3MtzJxaLpbm5udKBlStXtre3KxSKtLS0t99+m1QmYLPZzGZzWVmZRqMJCgoyGo2NjY1JSUmIi/SDTqerqalpaWnZv39/RUVFdXW1Vqv929/+9txzzz3yyCMCgeD48eMZGRne3t5/8YOYzWaNRsPj8YRCIQ2o/HXI5XKZTHbs2DH0w/DMPl8Q0JwplUqjo6PRfvXikhXKPzwWcrl81apVaIyhNbX/o1NXB+GH1FRgGANhNgM7YRgmJQX/BhYLHCAUMqTSr4oKSI6kpTFeBJuZ8nLIywxIrDjR3g6JlZgYSP1gUVoKoZfkZPyrvb1MYyMQo0h8rbXUZlsxd+6Kp56Sd3ezXxTLQnbs2EFlqhcElLywWCwff/xxR0fHkiVL/Pz8DAbD8ePHrVZrqCO5hqBQKA4dOsQwzPXXX++a6TMYDKdPnw4LCxOLxV5nPzOkU7D46KOPXnzxRfSzRCK58847MzIyRowYgfyasOjs7KypqfH19bVYLAzDdHd3Nzc3L168eOCRfX19a9as2bdvH8MwwcHBkyZNWrZsWWpqakhIiI+PT1RU1LPPPnshXxv+o8nl8rfffnv//v3d3d3umRPFhQaAKc4fbJAYRYjZTezChQsvyvRI9aeeiby8vCVLlqCfN2zYgDb9Z6G+nlGrYe3HZrhtNid7SEoChoFFSQkc5tjsYlBbC6GLUaPw10fswWolnq7VAjuJiCCSm7IyYEjp6XhyYzDA6UIhM2YM/vSODvgGYmJYduJK12CYRUQsuvHGFS+/jD+dYgDq6+sfeeSRtWvX/vjjj1u3bmV/n56e/s9//jM7O5vDgdnm4MGDr7766uTJk9VqtVar3bhxI1p06+vrn3zyyYKCArQSP/fcc3FxcSiPQzrFQaHr3njjjZ9//nnEiBEPPPDAnXfeyeFwmpubjx07JhKJ3nvvvVdffTUhIeGcN//bb7/dfffdSUlJSHBaVFS0cePG119/fcSIEf2OtNvtv//+u9lsrq2traure/755319fbHXRB06vLy8VCpVe3t7kiOI+OWXX6IEqJtvo6Cg4LHHHgsLC7vnnnsyMzMDAwMDAgL6ETKKi8I8WPkX8hVl1ejOlEdlJexwHOFVjC6tpwfCq+HhDKn3SlMTJIgTEzGaOTRHVVczwcHSqVPxp1dXw1tMmICP/prNMIX6+hKD0yoVxI9jY5kBz7AT5eVwexMmDHwFPr5Wy9TVyQwGRiyWy+XHjh3Ly8tjM0HoS7sI+n00SCg8CUePHo1xYOrUqTKZDHOESmU/dsyOfQmhqspeWGhvbSUecPq0/fhxu06Hf7WpyV5QAO/i5vonTtiNRvyrNhucfvq0u9MLCoinWyxw86WlxNN1Orj5urqBr3zxxRdTp05F315MTMymTZuIF6E4G3V1dTk5OSdOnOjo6FixYkVMTMy6devkcrnJZGKPqaiomDlz5ldffWWz2VpaWm6//fbCwkK73W4ymdatW7dq1Sq5XN7Q0LB69eoHHnigvb3dzSl2uz0/P/+GG2548803y8vLGxoa7rzzzt9//931fubNm1dSUnLOO7dYLOvXr583b96MGTNOnDhhs9nef//9devWud75QOzZs+fhhx/u7e11/WVnZ+fKlSvlcjm6gX/+85+dnZ0vv/xyTk5OXV3dV199lZSU9Le//U2tVrv5aCdOnMjOzl6+fDl+8FKcB2Qy2apVq2IIuP322zf961/2/Hx7WxvxEiUlMI2QYDDAFNrQQDyguhomGdIjhKa4yspznK7R4F81m+HeysqIp3d2wu01NxMPOH0aZmCzGf+qyQSvDpiBZTLZF198cfvtt7t+k0ePHrX/WVBO7WmQy+Uo8pGVlXXkyBFMlKyrC4i5WAyqUizq6oCbi0QQfsBCJgNinpAA7Bt3BxBdCA8n8u7GRkiOjBkDwlIsSkrgJZKqo64O3t3N6Q49BzEvY7XCtsbfn8GVRSxatGjHyy9nnUk5bdq0afXq1fjrUOCg1+tFItErr7zy7LPP7tmz54cffmAjrCaTaffu3SqV6tixY7m5uWvXrhWJRKg4pbe3t6qqat68eRKJZOTIkWvWrLFYLF999ZWbU9ra2t58883FixcvW7YsOTlZr9crFIojR464duQyGAxGo/Gc99zR0VFWVrZ69eoJEybk5eWpVKpDhw5lZWWdU8Ch1WpRvsYVvb29nZ2d6GeNRvP7779/+eWXDMMUFhZu2rTp+uuvb2tra21tdfPRMjIy3n//fa1We/PNN7/66qt/3dNvuEEuly9evBhVt7n+Pisra+XKlU1NTTvef3/FzJlQMUcSrsnlMAe6yXmVl0PNHemA5maYZkeNwqe2GQZU83w+M3Ys/tW6Ojg9MRGmqYGwWiH6y+USM+M6HYSfQ0MZbNwFBWZ6euD6pKo0FFkZMAOj5MuO3Nwj77238oEHGIbJz89fvXr15s2bmT8Fyj88cODBSJswYceOHZgj9Hp4uN08mo2N8Pj6+hI1oe3tTGsr0BeXjP4fUCpB9SkUEk9XKuEKMTEwerGoqIC0Tloa/tXmZqazE6gDKStUVQVBxbFjiaKTigp4icRO6uul/v5vbN68cuVK9IudO3f+6dE1DIFaUQgEggceeGDjxo0ff/zxli1bdDqdg/d2VVZWvv322+np6RUVFdOmTXvxxRdRgUlPT49arS4rK0PLuUgkSklJUSqV7e3tpFOam5sZhpk/f76Xl5dOp/vss8+0Wu3Jkyc7OjrQnfj4+LAVNxqNZs2aNdXV1dh7Rr9PTk6eNGnS3r17n3/+eS6Xm56e7v6T+rusDRUVFc8884xOp+PxeN7e3nV1dej3DQ0N69at+9vf/sbj8davX7906dJnn31WJBJptVo33waHw0lNTd26detnn32mUChmz579+uuvd3d3X6Q/kYdj586d06ZNY4UL6JcrV648cuTIjh07QFqu1Tqr6kiJOZRYiYpCunUMSkpg+SclPjo6IPcRHU08vbTU3RTX0OCc4kiZ8bIyd6J+ux32V0Ih0e+grQ0m8Ohooq6uuBh4iRvZX12ddPToFc89h/a3SDP35yZJyj88CiiCLZVKd3z1Ff6IigrGz4/4aMrlTF8fPOKO1DsG3d3AnQMD8bGTtjYYeFyuu4Etl0NYhRQaqakB9kMaWojcSCREq4/6erj/xER8YIZhoJzHaCROHDIZzB1xcTC6VqxwpSDIIpbCDfz9/YOCghAtQIvoNddcs3Xr1pKSkldffdVgMKAKDrlcfvvtt7/11lv33nuv6EzivKenx2AwfP3112vWrKmsrDx16tRvv/0mFotRBAJ7ip+fn0KhQCGW5cuXt7a25ubmGgyGU6dOsQcIhcKuri7HelHS3NzsyhhcUVJSMmHChJCQEJTMPnDgwDXXXBNO2hmfQUhIiEaj0el0Fovl0KFDvr6+3g6EhISwX4LFYpk3b96NN95osVhycnLmzp0bFBQUGxsrl8vdfBs6ne6HH37QarWpqalvvvnm559/3tDQsGbNmqHbZuyyYfPmzf0CligM/If63mCASYZhiFMcmoWCg2GewaK6GrQXpDlKqwUCERaG3JLwpxuNIFzDQiYDWV50NHGKq6gABpCcTNxfoeAxaYrr7YUJfMQIkirfyY1IdglsaMSxgsBCs2MHmic3bdrE0r7zB/f555+/oBMoBi1Wr179/fffMwzz/vvv4xVPxcXw1JJ4t0oFkQmLBZ4t7Pqt08H6jR7ugdWAajUMHpsNYg9YIzKtFoITQUFEduI+6qhWw8gJC3NXrNvRAXorN3Kwzk64PjZ20trKKBQw8s9knbKysjgcTn5+fm9vb35+fk5OTmBgIP7KFA7k5+dPmzbNVe8ZGho6fvz4I0eOTJ06VSQSoTCA3W6XSCTd3d2HDh169913eTyeQCCoqqp6+eWXi4qKnn766YMHD95yyy1///vfg4ODSadMmjTJbDZv3rz5wIEDEydORHrVvr6+kpKSadOm8Xg8LpdbVlb26aefHjhw4KOPPrrrrruuvvrqgVWsOp1uz549ISEhWVlZwcHBoaGhAQEB999/P4mssLBarXv37t23b98XX3xx7Nix1atXR0VFcbnchoaGESNGJCcn63S6wsLCRx55RCqVhoaGLl68OCgoiMfjWa3W+vr6a6+9lvTRAgICXnnllR07dnh7e/f29ur1eo1Gs3///uuuuy6StGxQOET3ruRDKpW+//77K1eu/GPY2myQmGAYd5YBRUXuHAeammAiGjMGP0MajcAP3DgCNDbCFEQ6XamE/xeLIfSCRWUlTMJjx8IeEouyMsjOkMiNxQJpIzczMGvH4CZ4fDY7CQwMlEqlQUFBaJ78fv/+5JQU/OqDA61/8RzExsYSq13YatiMDPzJHR3AHrhcWLyxxB89uyYTxOUGPv3d3TCwvbxgV4GNOppMMDb4fOK+ob0dohcREfh9SU8PUJ+gIGI9S3s7TA1+fsTESkcH7EskEvzY7u6GfQmu3Gb16tWo8CwrKwuf0qI4b9hstqNHj27ZsuW4w4t22rRpOTk5c+bMaWhoePPNN7ds2RISEmI2m12FF6RTULTAYDBwuVySUKOqquq1116Ljo6eN2/e+PHjsSUkVqt19+7dycnJqaQnkwC73b579+6vv/562rRpc+fOZUtynMK68yhXcfPR5HL5f/7zn/379yPxx/jx4++6664FCxbQZjTnU/HHbs0xZoYWC+ydSMKLykqYJCdOxL/a3g4EIjoaHzyw2SD2wOEQl39UkDJyJF5X19oKM7BIRAzM1NTANEWqWESRlb4+qCjEmdYATp0CakV6zmtrgRulphLJDdofpqdjRS2bX3tt0zvvEL95Aij/8CifMalUeuTIEeKzNW4cg+2F0dMDz65QCJoM0nOD6EtcHEb20dfnjItEROBHpt3uLNZNS8MrnjQauD6p2lajgXnB15c4crq6nCFT0rajtxeofWgoPvGk1zu3BTgnEqjLffTR/MJC1PKD9ou5KLBYLFwul41GFBQUsPzjPE/xJHjwR7tscA3+47cKzc0QgtVqYRrBToNNTZDeTU7Gx191OpglRCKsbh2AjKTT0vCa0/Z22P+IxXjhXbtj+xQcTMyM19fDBB4bSwzbID8F0s2f0++guRnoUWIiUbOiUMD/jxqFl/3ZbPKDB1e9+25+SQmiIPhlaACo/sNDgGrc8cadqD9LfDx+1Ol0QGyDgoBAkMhHZSUMLazmFGmt/fxAFEIKDldWQsZ0zBg8+bBagb4EB+PJB+vBStqyaDRwA25inkYjsBOS6sVsdmpiCDZo0sDAN/7xD/QzFaJeLPB4PNflNjQ01NfX12Qynf8pngQP/miXB4sXLz4H+WhthW2S2Qw7KOw0qFbDMVIpfv2222EDExBAJB+nTwOzGT0aTz50Ogic+PnhyYfakVl2L8vr6oLpl0Q+FApgMCNHEskHUuW7yby3tbE+0Rh0d8NbREXhyYdDdCKNjn7jvfdQ2EMul59n2SDlH54Adl3EZF6Q2jkiAi9oMhiAfAQGQliSNLTkcljCg4IwmQuTCdZ+Ph+IBakUraYGKEJiIjGsV1oKMwKWPZhMMHLsdqIFO/LwcVPJZrPB1ODlhT8Aicm9vYlZG4dDvHTUKPTF5ufnUyHqpYC/v79er29ra7vSN0Ix9ODaxxsF//HLJ48H6ytWHIaqAkUiomi0pAROJ00yzc1AbhIS8MIyxF2EQnz4trsb3trHh3hxpRIm8NBQoh62vR1aaEmlRHbS0AC3N3YsPi/T1QX3T/aJhv1hbS18daTdaVkZ/Jua6vrlo+6ezLlA+YfnBD82bNiAf7YCA91pNr28nIMHuwNTqUA54e2NYSdIzCUQwA+k68vlkNyJiyPWepWVwftia70QdbDZgHxguQsKnNjtEFkhpTyrq4GjkCrdkVMIqdIM3Z6jDp4NLNEQyKVAUFCQVCr9/vvvXd07KCjOB7t372Z/xsyBbHzX0bzbnSEQSZXJ5o6xqK2FPZ5YTJS9FxURC1J6e2GC8vGBGQwrGOroAG4hFBJFIRoNRFbcsBOl0qnKx4ZGEPEKCYEDSED7Q1KXDCRZPfPlSKVStvPi+UyVlH8MebA0s3/wAyUmfHzcibHtdngE4+PxFSudnbBvsFrxI7OuDnhJby+8ig1potDLiBFEYo7SOqSBffo0xD+iooA/kQ4wGODTYd8dfUCtlmgWgt49OZnIXZCazMFOpFIpmtpoCORSQCAQ3HLLLXq93mw2X+l7oRiqEyBGnmW1wiQQHOycB7AoL4dhTip4qa2FWSIxEb896+yEPV5gIHH5LykBYoGNfGgdNiTI3x1rpdjVBaELNxM42oAFBBCZU2cn7AAjI/GKV4vFWa1D4hZI9ufGawT5HZwdWXnjjTfQD3K5/JwhEMo/PAT9yQcSPZxpXoBBSwvsDEwmYoO33l4YezYbZCUHLvD19fAvCpxggxOsUwipFquuDhhSUhKe+FdVATESi4lRQeQUkphI9DFrbYXE6ogR+MRTTQ18QFKpMLoBs9l1VmKntmPHjuFPofgLyG50UlMAACAASURBVMrKevbZZwUkKklBgQOrM8jKysJow1Fqo6sLyAdWmYEMgUjhB5kMlnBSYqWv7xzKs8pKWOOx5TBGI0Q+rFaiWRG6OI8HFydpg0pK3CVu2NgGaQZGBYkk4oW+Pa2WmJtuaYEJNi6u35dzQSEQyj+GPNByiKk0c7Q+wq+vajVkDb284OnEUmODwRk7iY3FsJPmZri40Ui0CNRoYHSRRZ3AytVqIndpanIawJPq4JubgT1ERxP1UCjxRCrnaWx09sYjmaiizsBnsxOpVIqcdmj8g4JikIDdYS9cuLD/a01NsH3q7iYSiIYGGOajRuFnobY2SF5IpfhJBuni3QQnampg8cbmdq1WeNXm2Nphg7usSRopNILSIhwOMTLBJpVImtayMrgBN6lnRC8SEogriEIBm0Pc7s41BOJ+tqT8w0NG4FlNyWtq4AkeNQofG+jrg+iFvz9sCLDLs8NhF5770FAMO1Gp4ApeXsSCF0Q++Hx3vWeVSiJ7UChgzyEUElOSra1Antz0l0EZX9LU0NICp0ulxHytXO70Px6QMc3MzITXUdSRgoJicJAP1JfkrNdUKuAWej2xrEOphEVUIsG/yvqEYrdAKPHBMERhWX29c4eDXbzR5jCaMAFaLH+wE/f1LG5cSsvL3XWZQJnrlBSizxgyqiY12XC0xnXTxENqMrEttNyHQCj/GNpg2eUfw08mg8FDWl+NRqfSGyspRairA2YtEGAer44OWP79/ODBxWpO7XbYVVitxIoVjcadPzHyYHXTmqGzEz6gG0Wt1Qrsh8PBk4+ODuA3ERFEobtaDQSFwOuRr5+8rS0PSb4pKCiuHNjOfP19B7q6YBRbrUAvsOIzpGwLCcHTC0fVG8R9SVug6mpY/kmBE4UC5pmRI/FGYbW1wIpImgzGMf2aze6qYevqYP/jxoIdebSTQiMNDUAvRo8mpp7tdiBApMQN8ngVCIhTtKP/KBuOcu/ITt30hjbQX/cP8tHWBv8vEhF9wOrrYfHu7gbyi00r1tc7LQIHspOeHnh2IyKAQ5zNrOvr6zkcTlxcnLPehFSxYjA4y+ixcm4k9uZwYGBj7w1JUtwLpqqr4f4TEzGaFbkcNj3BwcRpRaNxkjMSr7dYslJS8svLd+/eTY3IBjlcJz6ZTNbvl65NZVEHmVmzZl32e6T4S2D/mmcFP7RapynAiBH4NR5NI25km6Wl7lQddXVAIGJj8fSirQ0msagoPO9pboZJxs+PmFluaIDwbUSEu97jajWxRYZr3ge7/VMo4PSYGKKoH8lKSAUvNhukdXx8iKEXNIdLJNlRUcwLL7ApGNJsSfnH0MZZWsjeXlA2hIQQrTjq6yHsgfoXYMmvTAZDy2TCkGtHUsM2YkT58ePHOjrMv/4qkUiuuuoqZFj53XffVVZWvrZsWQBqWo0VtKKUJMlJrKvLWY+TlIS/N73eKUkh6a3Y0YtV1Go0QD74fCJ3YbkRaVZyuPSsWL58ydKlVAJyxbF582a0/LDcgl2QLrQJFsMwjz32WA3KuFMMHaBheBb5QMI1b2+iFzPb/JZEL9z3f0HRZRI/6O6GSSw8HJ/XRoqKwEDiDKNQwBWCg4lOG+3t7iQprlaT2O0fEm1ERRFF/WyHF5KFfHk5TNGktI5GA0tMeDgjkUgdimDky3Ls2DHKPzwZID41mWBcDYgNGAwGVN8Iu3+TyekAiCW/KhWQAJMJE5ozm5m6Op1Q+Pqrr364dy/765ycnFdeeQV14miVy3vl8oDUVGK1LTLbwFbbIrG3lxdRKXY+Vh9KJdw/dmpAYjE33WesViAfPB5x3unrg73LiBHRjo3Ln1jhKC4iUMvvP316SEiITqdjW/IyDCMUClHjaNIpO3fuXL16NbG5EsVlh9wBVpXlRH09jOXISHyCFU2SNhsMc+w0grq/kkzKkU8oiR/09MAkFhzsLrgrFBLJR5vDrcDP7xxWH+HhxNhJezvcYVQUPvOu1cKXExZGJDcotKPTEQ0RkNVHaio+smI2O9uLnrn/7OxsxD/y8vLwxtyUf3gGQHxaVQXr99nLZ3V19dKlS3k83k1XX50hlaYkJobExHhh61HVali/ORyIXgxkJw4Dn++//fbDvXuXLVuWk5MjlUqLi4u3b9+u1WqBf+j1up4eo0Dgrn0MMgAemLNEgQ0+H2YNRzTFYrEcOXIkMTExih1pyAuEZCHPJnSx5b6sWIzkAMhmTEkDz2SCKzhceqQOtuc+qEhxqcHasbD/6f54tiHnrl27du7cKZfL7XY7Sz7sdntnZ6f7K6B8jWvWhuLKgo1B/jEMkawyMhK/QtvtcADq740ND6A2ERMm4N+vsxNWd19fPIEwGp2TGDasgjLXPj7EapRuh1uBjw8xOmuxOBtwkthJX59TV4d1IkFG0oGBRM0f2r8h3T02/IxKAkmde+12p1WjS80Bywvd7NYo/xjacAaflUp4bgas7lqtVqlUarXaqqoq9Jv4+PgFCxbMnz9fIpH80XKipwceLz8/COsNZCf19YxAoOno+KWkZPr06X//+98jHAGG6xyA9b2316BSBQUG+pOCB8iCPTkZ82SjHYm3NwytM/UsfX1927Zty8zMXLZsGfx3bS2w8oQEYsUKyvgKBPjhzfqMkfRWp08DB3LjBVJR4To1IP6BP5LicuGC4hA7d+7ctWsX69INjTddyEd2dvaKFSvckxhUX7Zz5868vLw33njjPNt7Ulw6sFzQ+bdAqkyJhCgtr62FVXzECLyus7ra2ZoOqzxDAVo+Hz/DWK0wRXh741URej1McV5exGIZnaOFFjqAtEEqKyM2qWBDL/7+eHpht0PsGbmsktDTA7kbkosrKgl0Y2ONbNbOruZleSHlHx4L9KeVBgQMrBS32+1dXV035+TMSk1NTEjoMxqrtNrvvvtugwM5OTlPPfVUQkKC06YmIACe74H7BtT8xcenta+vorFxzpw54f3SKyaTuaKiW6fzCQnhY0vVm5qIZht2u3Pg+fsPjFtotVqr1cpVKuH0M+U8XV1dmzdv9vPze/TRR/3QJgaJ1b288CZCiFskJhKtPlAxbXw8UZCFUp4uQys6Ojo/P99NUpNikEAul2/evDkvL480A86YMWPp0qXn/3dEMX+ZTEb5xyCB0+qqsRFyr1IpUdmArJBJJaPIEIjkpIzcOJAuHjvFIZNQ7O4LBV9RxgcbObA4qm3tdqIRGcoKuWkTYbPBJMblEg9APS5IqWf2HkgFL0h0EhlJTKxXVMDHxHEvVgJCAuUfnoDojIyBVh9NTU0bN24cKRJNSU0VBgUxY8cmM8z8+fMVCsXu3bs//PDDBx54YO2zz84ID+egetqBkb22NhjVISGMVtvl719VVfXss8/2b9SJIivBwVyTyWvg8o+8OiQSvGCqthbYg0CADSp2d3ebW1q4ra2uvZHkcvm+ffva2tpiYmIWLVrE4/Fg5Fgs+HKyxkaIu8TGEivZkGRELMZ7pKJdkV4PQ9flo9G1Z/CjX8BjYMjKz89v/fr1t9xyy3lekP7RBxvQHxQya83NMMlERxPJB+ofS7IUksthoiOVy6J6fuTGQWrjoNfD2o/1V2XL8Ug2zbW18BYkzf45s0Is+yHljisrIcZM0pMioNQJNvWDFLVkqw/4gDodURRyLlD/D4+If+C4p7e3N99uV7a19ep0bNiQw+FIpdLHH398x44dPj4+H7z1VrtGAwNgYFyxqwsicqGhzqQgw8TFxYX1W6erqiA6MmoUw+WKxWKffgyguxumhrAwfDq2vh4GBpfrOinYbLaenh61Wq3X6/d+9929Dz00denS2Kuvjo2NfeGFF4xGY0pKyqZNm6ZMmfL9999rkQ2OTocfvS0toPki1eCxfSODg4m9G5qbISw5wH4e5TVpCcwgRF5e3urVq2NjY1evXu268epHPqRS6Ycffnj+5MNVQUIxqCANDARZhkRCJB9oC+TtjddtoM19VBRxlkAu6dHR+D0MyiyPHo03CkOVum6cPBoa4AA3HbJQk4qxY4kW7EgTmpSEX/5ra52JbzfkAFkZYWMnqFbITWe+xkaYIbFmBw5kk048Axr/8Fj4abVCR7RQkJT0W16et7f3lClTzgpRmEx6hjFrtczEiez+3mw29/T0cI3GIIXCSyoFUWdystFmYxjGx8fnrAwLautMqkTXaGynT/d4eVmFwiCz2bvf5qC5mdHrDX19+pgYvtWKxq7JZNq0adO7777LHpXf05OSkjJn/vyMjIykpCTEb6Y7AC8rFPD0YwODyDs5NJSoh0W8/szQstvtdXV1X3311eHDh8vLyyUSSe7LL4/z94d5DbsrohjcAY+srKx+tbjh4eHt7e2sdvVCc2eu8Q+q/hk8kPj4ADkgaT5QAzbUBmtgdLajA7LDIhFxlqivh9WdZLXc1ATzDylwgmYnN/sfudxZbUva/7BWH1i1LOsfT9KEymSwh0xIIKZ1EH8yGokdaqqqgFiQqm0VCmBv2AYdCPX1mW6Mmhyg/MMTgCkd7OmB58NuZ/z9m5TK9evXl5aWXn/99ePHj6+pqVGpVOVlZcFC4Yp77onKykLs1WazHThw4PXXX6939JZbMGvWs0uWiNLTG9vbly9fXurIQRYVFUVERAQEBDjbOju2BfquLrlcPmHChD/iH0Zj3eHDL33yyaHjxxmGSUpKevnllydOnOh8taXF0N7+6TffvLVnT3dPj7+//2OPPXbfffeZTCYkp01LTZU1NV09fvy/tmwJImlOkRNrYCAjlep0uu3bt3/yySf19fUpKSmzrrlmQVqaJC6OVWN1dXX19PTExMRwOJzCwsJ/v/12ZkzMvfPm8Rx6ru7u7tzc3P/+979arTY4ODg7O9vX29u7vR02LqRSN7oIDQ7k5eXt3r27X5tNqVTqSkSuv/76jz/+GP29srKyduzY8efei+qOB6P0Xiwmko/2dthjcDiwQR+o20D1qEFBxJIQuRxWd1K1LZoASaELFFYJDSVyi7Y2OMbXl1jPck6rDxTfJSVuWlshLOTmdLQJ7OoC+jIwOmKzgWyFwyGaLbFWIiR25bi96MmTGbeg/MMTgUzWHVluhsuNjIycOHFiaWnpIQfQIbddd90TixdLMzNRYtJut3/77bdPP/30TTfdtPHxx0/V12/9/PM9Y8Y8cM01ATbbyJEjEf944oknYM8hFidLpdmZmTfdeSc7vLhcrlMaYrPV/vDDqrfesvv6bt26lcvl/vvf//7ggw9ee+01IC6trTql8p3PP397586UlJQbZ86sqKh45ZVXIiMjb7311g0bNrz44ove1dXPvfOOb2SkDy6qCTSlsjJWr+cFBNgTEkpLSl544YWCggKJRDJ9+nSTXv/etm1bvb2fW7v21lGjQCDCMN98883OnTvffvvt3t7eR5cvV7S0lIWHp9944yTHq7t27Xrvvfeys7OffvrptLQ0L6MRNKdCIXFiam6+RH83ij8d8Fi0aJFMJkP6UNYU+LbbbmMYZsmSJeiYv0I+KP8YnJCSdth6PYxTux2fHNHrQRgREEAsCUFZGxI/YFO32KxcTw/wnoAA4gSCEtN8sheiVnsOq4+uLlj+ScGVnh6IzbjpMoH2b4igYOlLeTksIiRRS18frC8kmzV0e3I5cC+7nXgDDlD+MbSB5sT+gnyUs4yLQ8RWIBCsWbPG39//3XffjYmJeWHVqqtjYnhcLjydZxKTpaWl69evX7BgwTN33OHn5xcjkRw6ckTnKAYTiUSbN29etGjR6tWrxWLxtdOn1xcXlzU2/vD227lffPHhhx/2C730HD++8bPPGIFg48aNo0aNstvtxcXFp06dslgsjFptlcs/+e67t3fuXL58+bJly/z8/GQy2fLly41GI7pVQXOzwWLxjYhQtrcbjcaBDdlLTp5cunTph889lzZ3bnd394YNGwoKCu64444nn3xS5OfHVFQo1OoPjx79f2vXevP5t9xyC4fDCQoKslgsSqXyw23bAn18Ztx449dHjuSdOpUxbRqHw0lNTZVIJJWVlSdOnEiMj/dDba9JE1N9PShOKK5oSYtrwEPqgOtvVq5cuXDhQqlUmpeXx5KPv24dhuqeqAvIIIE7Lmg2O+0KR43CrK9GI5APgYBoNtjcDPEJUrVtZyes7iRVhE4H069AQJxAULUt6l3HxVXb2mxOrw5SaATJMkJC8D2wjEa4geBgogs2ugdkFoLlN6h9aWIiPu9jMjmvT7o9gwHYSUgI8I9z8XXKPzwOZWXwBCQkuEqWhELhqlWrxo4du/6VV15cv37tQw/NuPFGzhnubDKZvvzyS4VC0aNU5p886e3v/8W33zYolSunTkUH8Hi86OhokUh0w3XXPXb11czs2ZaxY0H+yTABAQHNzc1/2DdVV+edOLH36NH09PSioqL29vaCgoIPPvjg8ccfD3R0n1Hp9QePH8/JybnvvvtQAW10dPTXX3/tPL2xEWKecXEMn2+1Wm0O3Uk/+Le3+wsEOpGI4fO5BoNAIJg+ffoTTzwhCgyEacVmk0ybtmr6dK3B8MUXX2RnZ0dERHR0dKjVaoisWK1bVqyQjBtneOut+vp6rVYrFAozMzNzc3NfeOGFF198cecnn/xj7tzZ99/vhxV8oZinm10FxWVUeKAf8vPz2YBHZmYmSzJcycf27dsvYrE0jYIMaiCfMVRUMjD7YDZDwYib3rAaDQQGUNZmYGIC9Y4hWXEglzAul6gYRZWuiHz4EmQZxcXuvDqQzahQSOzPUl4OvIHkFIJQWUmM7yLRPUnUYrM5i2VI17fbndzOcXuuvRGwoPzDs4AU1/HxMPC6uhzlY85VnMfjzbvxxgSzee22bY+/8ca6kJC5YjGSo8rl8vz8/Efvu69VJlv+yitanS4+Pn7t2rUZGRnshYOCgsDntL0d+czwHEEF9JLNZoPYhkMPZWhv/7Wx8eabbx47duzGjRsVCoW/v/999933twULuA0NTHCwUavVWa2pqanItf0stLbC6h4VNXDW+O233xoaGu666y5ufb0PwwgCAmoVikzHpzMYDLGxsYGBgcDKjUZ47v39fazW0NDQsrIynSNWodPp2traGAf5GJORwURHx8XFFRQUmM1mVBM0bty4zz///OjOnf/dvXvVW2+9s3fv0qVL58yZ47QYcdWyicUwtdFF6DJi586dbLcX1nnM1dVj0aJF/QzEWPLx59SmWGRmZvYTmlBccWCGIfJKlkoxRfUmE6yOyM4H2zyWtfoYPRrDD1Bsg8sldoGoqoLJISEBn7ZAoQWrFd+g6jy9OioqgBWRyFNJiTsjEITiYmKDGySqi4gg1uOUlsK5pHcf4JZ0zkmS8g8PQlMTrJExMciqy8vLi8vltrW19fT0wGLv6OGSmpKSu27dy//3f08//bRKpbr//vt5PF5nZ2dlZeWKW25Z/eCDLzY3G+PiAsLC+pl58Hg8vsnU1tFhTEjwwVF7a3e3vaNDLxLJ29vj4+MffvjhRx55RKvV+vn5eSMTnsBAxmz2GTXKz8/v0KFDV111VXp6+h/vgnKioaFMVJSP3R4eHt7U1ISYk9FoPHjwoMFgWJiZ6afRBCUmiiIiKisrjUYjj8fz9/dXKpV9xcUCHg/RdpvN9ssvv3z11Vfz58+XSqVGoxHIB8Pcft11U7KyUMo2Li5u3759XV1dqH8ewzB8leqasWOvzs2taGv797///eSTT3777bfr1q2Dpr5n2u85W+NS5nG5sHnzZtc+LytXrszLy8OmWlzPYsnHXxR89AP7Lufc1VFcNvTPhdXVQXpCIsFUrKC4CGquibURs9kgtmGzwf4Nm7Wpq3M6iWGNkmtqYJYYO5boZNjQABdx09u2ylFMy+r0B6KsjOT09cfaT3oVobISroB1E+npgeSyo8sE8d1tNnfXR25JaWnEauEBoPzDEwA0s6UFcpYuA8/Hx0csFiuVSudBtbVAjbnc8MmTX0pJ8ff337JlS2Ji4nXXXScODs5KSdmdlzc+ISFy6lQBzirHT6mMHzGiqqNDYzL1G3wQGgkMbJfJjEFBwri4pKSkb7/9dubMmdnZ2RAjsVjgrYVCVMgeyePNmjVr06ZNt956a0pKijMKYrUyGs0N2dl3r1nDdQQkuFyuQqFQqVQhISEnTpw4fPjwA0uW+Pb1MeHhvOBgPp9vs9nsdntAQMA111yzZs2aVV1dS+bMCTIYavbu/fXXXw8dOvT3v/8d9b6xWq2MXj9p7Ng7Zs/mnQlajhw5Uq1WKxSK+Ph4hULx3Jo18yZNunn+fF5ERGpExJYtW/7nf/7nmWeeeeedd9atWwdREBSxPFc5O8XFwurVq1mekZWVFR0dLZPJWC6SlZW1cOFCrJ4DNYq76OTD1QKEhr4GKZDVMqm/K1p6SV4diECYzfj+bTYbLK4mE8wAWCcx9NYJCUTygXrbBgURNZuNjaDrHNh4vN/qnpKCN/NAr44bRzwdESCNBq4wkB/o9XAFUlqH7WIxbhyRW+Dcks6plKL8wyPQ0wOb8qgoVz0R4h8xMTFAAurqnFJkh6LKz89v5cqVRqMRNBxmc5ROd+fttz/9yisPqtX/MJnGjx/f19d38uTJ/fv3FxUVffbZZxMiIrz7+jKvvbZ8507UUNcVATZbUkREYW2t2t9f4u29aNGi/Pz8pUuXPvTQQ9dcc01AW1tFU9OBQ4cOFxU9+NBDy5Ytu//++9PS0nbs2IHMNtBFpqWnj7vpJu6ZqGZGRkZubu6iRYsEAoFarZ557bW3pKRwAgOZ2FihI33D5/NRue+8yZPNDz2089dfl774IqhD/P2nT5++ffv2zMxMFFzx0WofvP56WVqaZOpUdvAkJSUtXry4sbHxqquuYnp6tF1dj23e/HVp6cSJE9E9qNVqpVIZERFhNBr9UMPuARFL9x1TKf4680AMQyaTuXKRFStWkPIpLPlYtGiRa4O6iwL6tx6E+IMLymTOglisPKuqCoITbjqYNDbCASIR/nRkshwSgm+Pwro8k8wC1Go4RiAgVsSoHJ11R44kciPEb0ia0IYGWALGjMHHdRCUSrjJuDjMFZBshc8nVtvW1kJUKTmZmFdCzXujorBOa24GDsd+rgoZisGMadOmyeXyDcuWLVqyBC+HRsy0txf4x9ixmAeoooIRCu3d3Xly+au5ucXFxewrWVlZc+fOXXjddQJHqbdNLDYajb790qI6HVNe3scwdd7eY8eOReUqLS0tGzZs2L17N3tUfGzs9TNn3nfffX+0tGVRWursPevC6w0Gw2uvvbZt27Zp06Ytnj//RrHYLyiI9RhGchOorW1rA+Ll78+MGWOxWPR6vb+//1mZI40GmDvDwODEbk00GqaiokWnyz18eNeuXUhUi5Cenv7Pf/4zOzCQYzK5BkXZ8P6RI0fomnSJsi0s83CtsL3tttvcKDnYv8vKlStJ/b4vynBDzQ0uxfUpLvRv4SSaSiXMAyNG4OfA2lqYALFJGYSWFqeZEDbAiVZ3lHsdiM5OuH54uLvOtJWVMPGmpOD5QXc38JvISKLHeVsb0KOYGHxcR6kE7jVyJDGtw1qhkL6f0lII7aSm4vNKTU1wAwkJRCuR3l6gd6GhA8uF0F5CKpUeOXIEeyqNfwxtOD0JhEIi+UD922w2WIAHko+GBmDlOh1HJJo6btyXM2eqVCqZTBYUFBQbG+vv7w+0t6ICxp5E4sUw/cmHVouIc0Ba2niXVT8qKuqNN9547p576hoaGJMpLj09ZPRoTHcY1sF9QFBRIBA899xzTz75pMDbm4Pyji6CcOTqASNfJmO16DweD/xFBqrJeDwY2FjygWrV+PyoCRPWXXPNM888I5fL29vbw8PDR4wYIRQKOTU1MLrcd0+g+Mtg4xaIZ6B6Wld5qXvmgYD47l+vsz0fCxAa+hpEaG8H8hERgZ8DkUloRASRfDQ0gFRfIMCTD5kMyEdAAJ4c6PVwur8/kXyg/t6o4AVLPsxmoC8kKxHWTSQiAk8+kNNGZKQ78mGxOAuGsd8P6tBJag+OmBm2ksg1cePnh69VRjCZSK9Q/uERIMmV1WqISZrNEPkYKOduaYEVms+HJ8/h08fj8ZCbwlmV6G6MdOrr4RicmJwjl4f4+k5KTobn3o29cV8fyT+Yw+EA3amogMd34NYBFcIhDx9sStJmg6wTlwsyeGx7OZTTtVpZZiYQCEY5cJa/8ujRpKgj7YN6sTq2sOak2dnZrgrTgYUtbrBhw4bzP/gvWoBQDBLI6uuBAYSH41WTyOLTfR8GtRoGOLagVKWCV/l8PDWx22F65PPd1ZtUV8NhCQnE/ttl5N5v7A6KZOaBWpeTjEBYlJbCW2CLVpDfAak9eEeHs+KPRG5Q4sbLi1SOm/frr/A/pKwN5R+eDKRnRqmHgWlFtRr2DYGBzvZFWJSUuEsKVlURibNSCY81jwePJmnkIy+NuDiiYotVsztKas/6vU73R5kcKeVZWwvDIzCQ6CGI1OajRuFzrioVEH83lXIUfw1yuXzVqlVoOWeZh2v+5U+QiUtNByndHHQwGCA6iw0/KJUwy/n6Ep24UFEbh4P3IO/ogDmKyyWSg/Lyc9TK1tURBa0IpaVwBRJ9sdkgccPn41d35LTh7+8u8IBuktReTqVie2hgXu3rg+UjLIwYmEHsCm1usZMwKhdybCVJF6D8w0Oh1ztd9kaNwizwGg08HBERsLqTyAfqi0hq61xXBw8olji3t0O+MDjYaaKHBfLSwLaOY6FQwN5l4PAwm50dsUlqLBRTNZkgpkqKi6LOk6TWlD09EHcdMYLYVJPi4iVcNmzYcOzYMVfmcT7ZlisCyZl2HjT0NVhA8iFtawP24OtL3D6x08jYsZj2rT09MEWgzRt2+376NGRv3dSaKhSwBwsJIdoVVlXBHOXisdQfZWWwfyPVu7qx8ehXFINNH3d3wxQXFoaf4kwm+IDBwcTIN9ucLy4OXxDkaJ4nd3R8n6vQ7wAAIABJREFUdAPKPzwRViuEB+x2eHoGrq8mEzw6ERHwCCYl4eu1Tp92akKxkMvxzADlI5ubnRcn2dScT9iwsxO2LwOznna7c9YgOfSh2+vrg89FKpdF909KCaOMbFAQsQ6eLWmmuBhhD5aIuK9tGQxgOQctwR0swE5faBby9obdF4kfVFfDFIetp0UW6V5eMH9ig6NIU0La97NGXv7+xNALah6eTDbyqqqCici91QdpfkaQyWASxtYcoPgxyeLdbofAjL+/OxNV1Lw3PByf2lapYJJ0nxVygPIPT0D/rdjp0/DsjhyJj/vV10PQor2daKSDRldSEt7jr70dHi+sHkqlgmEvkcDYI51utaKKG2JoBMla6+qAAQx8gmtqgD+JxcTACTJRtVphbGML5VtbYW8UGEiMK5aVEf2VUdqop4d45xRu0a8hy65du9iwx8W1SL9EYC1AKAYvEPlAoV8SP0AtTmJjMbJKpBhFiWNscFSlgjlw5Ej8vp/NXPj4EPc/KPERF0estq2thYuQ2r/V1MAWbvx4xg1Q+1ys7h6JNnx9iRbvxcVYu4H+zXsFAvwU2tUF1CcyUo5Msd2C8g+PQ20tPJ1Y+2HELXg8p1UOVnOkUMCzFR+Pf7W7GyRL2NCFXg9PvEgEKzTWvRihrAxuwM3DjXpHYVsMNDQAcw8NJYY01Wp4d6sVph7sDajVwNxJWneUkXXxD8afTsrmUriFqy2pa9jj0pXLXnTQnMtgQ/9AlNEIsnEvL6KuC4lS+/rwexi73dk5nORBrlY7M7MkSabJBDMwqX0Mm/iIjMTPzyi00NkJMzA2udzY6IxqYC/uWpUTFoafJysq4F/SDIwmQDeRFUTvSN37NBr4+KGhTEyMLC+PORfIXmkUQxGNjbA7J1W6t7TAo6nXwwHYeioky5BI8GNDq4VnC6t4slhg3I4YAc+fG5Mf1urDDSoqYPQOjEzK5fDRhEJiWqSvDz4gw8AB2NRMby/cpJcXsWSmshLYD8n/WKeDbY1IxE5MNAh//ti8eTMiH6g4FoU9srKytm/fPlTIhysFoS1wBykXRAbqUVHE5KxSCbEHR58Hd6L1M0Kfs2CxwLoeEECcglBax2aDGRLLHs5ZbdvhEL2Sdo/Ipiw2lhh6YVWrgYF46UZlJTAkUnC6ogLu0I3dAFoCOBx8YgtFVgb4RLth7ZR/eBDQ0IqMxEuK1Gp4dhkGohdYdoKynmFh+LGH2i6TFE9IMNHTA9sCEq+vrXVafbhxCK6qgn8HqlJQzNPHhyj2NhicelvSxkWrhftH5IOk1kYef1hYrc5RTS3YLxw7d+5EhGPlypWspdjKlSt37Ngx+HMuFEMGdXUww4jFxCmosxPiuwEBeFlGYyNMIz4+RNE6qpUlCVrRDZhMMH9iEzfnrLbVap1xCyw3amuDwIObaliE0lIIjWBvsqICNmmjR2P0tihrr9NBOQ9pfnb1Mhl4BbsdPp2PD7tAnM/2jOZfPAUdHc7AIJY9oIKXwEB4SrBs1GKB9TUoiLi+VlXBuUlJGNqLkp0GA1B+UmakuRkGP/bBdb0O0p30O0athlmDxyOSDxR94fPhBkjkCdH2uDh8XgnFPM9uXnAWSkrcNcWmIEMul7Oe6IiFXMSetJcfyIKMhr4GHZRK2P+Qkg4oPlpXB+Fb7PIvl8Pk40a0juoB3Vh9oAAtqaIEMQNH83D8q2azO7MlvR6mUDeqNdcGvNj2cgoF0IuYGLzfAZp73Shq2dgSyTEB1RK7qUbGgcY/hjbQPBgdHOxMDWADgyYTDLyAAHfCi7IyePJI6ytqPoQ125DJYPn38oKHjxSWbGmBAAap2JU9pqMDxl6/0GJ3t7N5zahRRB8blFXx9ibKuWtqYOSQsk7t7c6YJ+n2Skrg+hc4tCjQ87l48WK0bCNXsaysrCNHjgxR8kElqIMUvb0wEZEsPpEuBHVxwk5xyCnEarXHx2v0etTe4SxUVzurbUmorwdhuxsfalRt6ya1UeaYgUnBlcpK2Fy5Cb2wngjYLWJnJ0xxJEMB1DqHVEnLXtxkgitgY0sVFedOrONA+YdHoLERcook5o5iAyhph0VZmTvNUW0thE9GjcJEDlQqpyZDqyW+u1brjHm68dJgjfb6PdxqtTOrMtCCjEV9PTz6qJSOdP8WC3Ff0tcH3154OHHbNGBo0RXo/LFr1y5kVc46nF7cnrQUFE7RqEBA3D4ho1KU2B2oe0Cl/kYjExX1xbffpqSkPPjggx999FFpaamzGxSSfCYm4jUTiP2o1fAqaYJFvW3dsIeyMnfBg6Ii2Dq6KdZF4Q21GjjEQN09slkLCcHHTlpb4eOTFCcIMhksAUFB+OhyTQ28hfvEOgE0/+IR8PMj1os2NEBEjmyR6+zAQio0R+0PYmMxsQG1GvhHQAAkJpOTiSboKKjoZuzp9XijPbMZBhWHA7yBJGiVyeB0oxGuj50dkM8YqX2DxQI7m6AgYsa3pgb4E6GrNRUhnhNsea3HkA9aAjPogLoouFmeUfg2NRUTvkVtHLy9YfciEnV0dDAMc8gB9Pq0yZMXT5t2/S23CEk2zcgi3csLpiDsAqxUwgzpptq2uhouQmptX1wM/Ik0P7vqWrDCF7PZnU1qZyeUC0VEEE2i2WphX1/8JNnYCBUxOCuHP6bHvj7StSn/8AiQtv5KJfztUeQDuzyjtB+psXJ7O7DjiAiM4qm3F86Njoa4RWwsMWuIZBNuyIfFAgEGrFq7thamlagoYmRCpYJ9idFINEKVyeA+fXyILn7urT7Ky4HXjxmDd0mhOBdYkQQKgXgA+XC1QKUYFLBanU2aSIO0pgb27mPHYqYIgwECAz4+ML+JRAaDwWQyPfHEE9nZ2dHR0TKZrDAvb8/u3Y9t3hz80Uf33HPPQw89JOwXA7bbnaoIkrINJYbcGD03NDh9ILFTKDI4dyM6QQyjvh4yy9gtVnk5MXbC1sqSTNJYRwMuF7/EKBROauUmceNorEV6heZfhjbc6eDUauAfKCqIfbjlcqfkgmT10dSENwFD5u5SKTyaCQnEoYVaD7iXTZCynkjKLhIRyQeKmtpswH6w0RHUO4phiOSjtBT+JY3tlhYgHxER7trTULjFrl272J+hSToFxUWHxQKDlFRtizxA4+Mxo9hqhUnG25u1SP/hhx82b94cHBw8ZcoUsVg8Zfz4h6dN2/vOO7t377766qvffPPNJ554on/IE6kiSF7MVisQiOBgd83J28lWZqj/JaE95x8oKyO2n62ogHvATnF6vTMy7aZ9DFLsIjulgRtUpClxYwWp0zl/IPefo/zDQ6HRACm2WmF5xj6+qNA8Kso1ZFdVVbV//36LxWLXaNpPnDheX6/w87OhHkIO2Gy2rvb2joICc0QErO4ulWY6ne6bb7555JFH0tPTY2Nj/7Vqlam39xzkA7kIDzymuRnuPyCAOG7Z5rdhYa5P/x/3MG5cbGbmv7ZtM8XEDOReZrO5Iy+vq6PDRopqdnUBtY+IcFfoT3Eu5J0xIJJKpUNXcIrNv8hksit9IxQOeHsTt+9tbbAJOXuK+wOoIE4gYCcZgWObrlAonPpTR+83XlrapEmTtmzZ8sYbbxw8eHD79u1Wq/WsPg+kgn8U/XUTXu1y+oTi62lR/0v3Vh/sJgob3qitdRoKDHQqM5uBmrjUyhLzSijyMTBzhCyqSUEXtPvt6mLOBZp/8UQglxsk28TGNpBDsEjUrxb3+++/LygomJySsve//13/6adavd7f3/+zzz6b4Cjoqqure+mll1BmNCk+/uWnnprooA52uz0vL+/VV18tLi52BBRSxiUmBvJ4nNGjXR/97u7uDz744NNPPx09evTdd999Y1ycn9nMNnCy2+3l5eXvvvvuzz/95M3lTpsw4fb7758aHc0/wx5sNlt9fX1kZKSQy9WUlm7dt++0TPbk88+j4Eb/e4iLGxcXFxgdzTn749tstgMHDrz+0kv1jrjRggULnn32WVE/P9O+Pvj2QkKI5AOFVSjOG8hzjILi4oOkeezthfiBSISXTDY0wCR5tmI0xLGVEgqFJpPp29zcyaNGSW+4od95Op3OZrNxuVwgN21tTFCQISysp7XVz89PKBRyXAQc9tLSOoXiq6qqw2vWlJeXSySS3NzcceyGx2h01wMLeYySqEm/mhqsEbvD78CemAj38NVXhw8f/uMeUlKAfHC5bFzEbrf39vaazWahUIhIGMSVET+LisJb1KPYCSnv393N1NfLKf8YpkDd4xIS8FFBg8FQWtrU2yuKj+eeeUR8fX0FAoFIJNJoNPs++2zLF1/cdeed11x/va+vb5KDI9fW1q5atcqu129dt47L5//7888/+Prr16ZNCwgIaGlp2bBhQ3Fx8dNPP3333XcLtVoY+bGxrj7larX66aefPnjwIMMwxx24Oj193csvxznohU6n27p1a25urlarnTB6dIC/f6VMdu+99+bk5KxduxZl3FUq1f9n70zAm6rSPn6zNk3TJXSBNuleSlcpi7QFREABhRGRrcryqSOLjoow4MAwgriMooCgqOwgOCpYEJFBBaHjCEwBEQS60r1N13QhTdMmaZbvOTnhEppzLjiDtE3f3+PjA/T25qbNPfd/3uX/Ll26dPTIkXOHD99w4MC2AwcYhvH/5JPly5dLJJIb17B48awBA2SenmjduXlfYrVaDx8+/Ndlyx6699733n77YmHh9u3bDx48OGfOHMcfDvrpcUy1bm5GoRHgNsA+YwzDTJ06lXEtwP+jS2Mw2OvKibnXykoUXrVYaJGJE599tnDNGh9v7wl/+EOvXr2ys7Nra2uzs7NHjBgxa9YskUiE0iJlZUaRaO/p0+vWrbt27RrDMC+88MLzzz8vtVWZXDt/fvM//rHn2DGdTufj45Oamuru7o6+EdPezmRnW93dM9Xq9cuXX716dfLkyTNnzoyMjEQKBkuTXr1a/fz27tz56aefFhcXx8fHP/zww5MnT75RflRS0lRVpQkMDOHxeFbrhQsXtmzZkpyc/OSTTwobG5mammteXpu3bNmzZ0/Ha8BJmes+Y2q1+t133/3yyy9xbdPKlSvHjRvHKyhATxCZjNAzaLGgM3C0Cmu19sAJd+TGBugPl6OoCD1EQ0LIXhcmU+W///3njRvP4MDddR555JHVq1d7eHj8YmPZ4sVz//Qn4fXohUajee+99xij8b2lS6Oio6063aWamosXL+JApVwuj4uL++WXX86dOzc8KSmex+P17t3BYvXnn38+evTo6tWr0Va4pubHb75ZuXv32x988Pbbb/v6+h47dmzdunWKwMAPX3pp5IAB/IQEo1B46tSpd999d9WqVW+//bafn5+7u7uHh4epru67s2c///bbKZMnV1ZVnTt3rqqqKiIi4sY1/PTT8ODg+IgInlNQ9MqVK++89dbk++5bvmyZNCIiJD7+xIkTrWySkq0V53BJwTO7oSKkB/eMgPLo6h8tqxXdxbTEh1qN/jOZqCWfzc0J4eFJCQm/ZmV99tln+N98fHxWrFgxY8YMJC9s47tNfP6OU6c2fvzxzJkzJ0yYcOLEiR07diQlJY0ZM4YpK9v/zTebDh5MTU3961//mpiYyO8QpMnKYvj8w0VFy5Ytwy2+O3fu3Ldv39KlS2c+8YQwO9sqlV5pbX1t9uzz588rFIrhw4cbjcZNmzZt3759xYoVkyZNEtbWMmr1N7m56e+99+GHHzY3N7/44ouVlZVZWVn9+/YdLJEwAQH7jx/ftGlTx2u4cgU9HeLj8Xuvr69fvnx5YWHhmjVrgoODP/30061btybK5Qo3NyQ+iHswXNVHM2vANtNWK9r90tqVHQD94VpLIa63UiqpgbusLLmX1wOPPCL194+Pj0+0fYzKyspGjBghk8kCbanN1HvvfWz6dFZ84ET+kSNH+kdH/1paqq6tPa9Wb9u27aWXXvKyPYmlUuny5csDAgI2b948/fTpCSNHzn/55UirlY1Gms3my5cvp6SkjB49WqjTMVVVD0yYoA0MXLhw4fjx4ydNmoSDfi9Nnjx60CDczCJmmNGjR0skkpdeeunEiRNpaWmtra0t9fXfVVQ0a7XPP/vs3D/96ezZs7NmzaqsrIyIiEDXsGxZAMNs3r9/+l//OuGRR+bPn2/fT9gwGo1f7d1bWVOjiY8/U1oqqqz88ssvS0pKFi1adJNJgMWCbk7azG5c6sVhZAI4gG0/XEl8AN2Ay5fJVWW2jRTKvIjFKC5C64bVasOTkt774INVq1b99NNPY8aMeeWVV0JDQ+0rCTYzNJszqqs3fvzxiy++OHfuXKFQ6OnpecwW7UBJmdrahNRUxfHjubm5P//8c9++fXFQxLHoTRMa+s+PPx48ePBbb72lVCrr6uree++9d955R97cPPH++68FBq596aXz588/8cQTL7/8Mk4QV1ZW7ty5c+XKlSKDYWJUFC8oyFuhMJlM1dXVO3fu9PLyuv/++w8dOpT57beDnnqKFxaWkJCgUChuugY89VehwK1ARqNx8+bN2dnZ7733XkpKiq3mvmrbxx8bGhvR9pUYOsIZH1rZHB6CweejohCaY8LNgP5wIdRqVLVEM7nDFVUmk3TgwHmpqfPmz+/41fJygS0YkDxsWG+H6IVer//p2LEJw4bFJCS8t2lTpVrt4eHxxz/+cfbs2SgPakMqlS5YsGBKdPSBU6f2ZmR8+cADU6ZM+dOf/oQVgNFobGhosFgsFr0eKSS5nBca2t9sjo2NLbdNytbbNgGRCkWH2XVyudzDwwM35RtKS1tbW3NLSp6YMuXpefPEYrFCoYiNjW24Xo0hLS9f8MQTU/7whwPnzu3du/fLL790vAZVWdmZU6denDGj1mR64YUXdDpdRETEq6++OmjQIPuL5eej+4c2HAE34vP5qJ4LdsBMT9cfEAXpotiWOPLuHPsMicVoeSTGhrHbmG2sfCTDbNy48aOPPtq6dSufz2ezwGhzbzRqAgL2b9tm61+pzszM1Ov1e/bskUgk/aOjkR9G797J9967WaF47bXX3njjjfT09Llz544fP96uANramHvuqSoqunr16ty5c/HdERAQsHjx4trCwv0nTgyfMUMoEEgkkuHDh//5z39mq9MUCsXixYt1Gs2Xe/emrlgREBxcf/RoQ0PDG2+8IRKJ3n//fYVCoa+qKq6t1SmVMoZJTk7evHnzjWuYPHl8XJw0Npatxs3JyTl06JBMJsvKyrJarcXFxR998MGDAwcGyeUoeuFcWIP9VePjyf0s7e32tItcfouyFQeg/8VVaG5G0t7Xl9ozgm1MY2LIjfI22Y4rNgQCgWMhVVttraq4OCA4+NlRo346evTy5cuXLl1asmTJTaLeFtlT9O694M03jx079sYbb1y8eHHixIl79uwxmUx6vb66uvrcuXOvvvxyeXMznr9gMBj0ej3+Vg+bQU2F0Wh1WBcaGhp2794tEAhGjx7NVFdrqqvLa2qiwsOfnDsXv7Svr29gYGBFRYXVakUri8XC8HiK5OQFCxY4X0Pjzz/nlpUl3H//mjVrLly4cPny5RMnTqBMJ36nePhcWBhVtmdno3WNwz4ZcAIbxcKjGrhLFBWhJS4ujpBYsVjQEiEQoCWOuD3DWyOGMfv4oPXElnNZunTpunXrzp49u2DBgqtXr9r78oKDC9Tq8+fPL1iwoKamZtasWXPmzNFoNKtefTW8tRUlZ23BknvuueeLL77YvXs31g0TJkz4ctOm1upqPP+yubm5pKTEYrHg10KlbNeuDYiMrGtru6bRmM1mvV4fGhqKA8wsbgJBL4tF09bWanvAt7a21tXVqdXqpUuX9uvXT1ZSEq5QNJjN7e3tDMPcdA1+fovfemvC8uVfZmTgjLPVaj158mRYWNiMGTPS09Mff/zx5cuXD4uLe2nKFElcHGEPplKhuvvISLLTEvZBEQjQw+X6A+h2esQg/tGNufELxsNpfXyoXhfl5aimOjKSavVRWop0se1hrNFo2tvb7dVSra2ymprYhITD338/dtSo1F69vEm5id1r1lzKylry+utBtgLy//u//5s8efKmTZveeeedqKioOFt72NiUlDaD4ZFFiyZMmNCnT5/jx4/X1dXFxMQwJSX9Q0OHDx68asOG8ubmwYMHt7S0nD9//siRI25ubm+99VaMvz8K7fB4DI838//+D32LDalUGhERUVxcrMvPl5lMu7/55lJd3ZK//CUoKKjjNQgEYX36pKSkHDhwICkpqU+fPvYy7+s/RxSY5fAIKizEu5bf+PsBXBAwve2iVFSgB2RUFNluoLgYPSM9PMj9omYzk58vEIk8PDzUarXBYMDrg1AonDJlSlhY2CuvvDL/j39cPW9e8qhRTO/eqsxMgUCQkpLy7LPP6nQ6i8WCml8uX+5QlSkWi0eOHDlixIicnJwt77//8urVh5OTX3/nnXBv7+rqamyK4+bmNmnSJHF1tbmhQS+T4RVYKBR6eHhUV1drtVp2pbJYLP/+xz++/umnx9LSlEqlwWCos80znz59+pAhQ/CEmvAhQ769cKGpqQn38tivITFxxEsv5cyeveXIkZdffvnw4cOvv/56YGBgdXW1XC6fPn36M888o62rcystlbi5oZ+Pc32bWo2sSmjzs9hmZrPZ0SM1ODiYrUCnAfEPl+DqVXTX0RrNcV6G2EmFnUJwTWVERJ8+fQYPHnyj8sM2V1YUHj5t2DB/f//nli7dtGlTTk5ORUXF0aNHFy1a1L9//48++gh7nB/48cepTzzx97//fZMNdoCCWq3Gr5IYEfHetm1jx4797LPP1q1b5+Pjs3PnzjGxsYxGE9Cnz4q//33s2LE7d+6cMWPGvHnzjh8/PmvWrP3796fGx/OKixk+PzEp6YONGx999FE2NiMSiaZOnapraGiurERF4/7+Bw4enDp1KvEagh54YMaMGadPn543b97hw4crKipycnI+/fTTGVOmxD344MWqKnKfHnYBwpN7OSZDAiSSk5Mh/gHcDerr0RJHe0CWl6P9g1BI7RfNz2eMRu+EhBCn4DGPxxs8ePCHb7/tJZG8l55eactKREdHi0Si/fv3t7S0eHh4eHp68nJyUIjletFJZWXlH//4x0OHDplMJj6fnxAc/P4zzxzctEnd3PzRRx/hCER4ePjYsWNXrVo1c9q0Dz7+ePnnn3/yxRcRERG+vr6enp4jR47MyMhYvHjxt99+e/r06U8++WROWtrTr78+Zvz45557jl2iBw8e/MQTTwhx2V+/fmGRkQ0NDVgi26/hiy9MV6/yvbwSHnro/fffP3jwoFqt/uijjywWS79+/U6dOpWRkcGYTN5qtUQqRRswZ68UnQ7tTmmdzOyID50O7X6dvUY4gfiHK6BUKKg+nlot+nz4+ZE/PbhRTSLBsl2pVK5fv14qldqDH9idV6OJiovbtGPH2rVr37GBvzUiImLatGmPDR3K1NfPnDOn95AhH3/88datW9lze3h4PPfccyNHjrRiJ7SAAH9//3fffffVV1+VSqWoHru8HC0cEgkTGxvDMGts6HQ6gS39iU6h16OErlzOWK3CyMgHnZaPWD+/rYsWoZNHRs7s3793cHDHa3B3f+6xx0bOmMHj8SZOnOjv77969eoXXniBPSAlPn753LmxTo3+N7kAceRlADps5YerVoEAXSLHp9Oh8Ia/P3mJq61F+weO6ZuFhcipMyrKx2oNCAgIDQ290SiLaW2NMplWPffcB//8J05tREdHz549e/Xq1VVVVbNmzeonFteVl5+9du27VavMZvOHH34oEol0Ot2CBQsOHTo0MClJUFvLSCQNPF51dXVAQIDBYMB2Z/Pnzx+VnLxm3bp1v/7q4+Pz3HPPzZ4929u21Dz66KPt7e3p6enPPfccXseGJybu3b07ecQI3Mni5uY2b968iooKBY+Hdpg2E/TY2Ni0tLTS0tL77rsPKQetdsGyZYeGDBl4//2Cf/0LJ7XZa5gwYcKpU6f+9re/5Zw6NX7o0ICgoILGxn9t2/bDDz+MHj16xYoVbm5uqKoDW33QIusVFWiVbmtDBxBTM5yA/nAJaN1QRiOS9sTpKmyjGo/naJ93YwdQWIiSeSYTOiA0NIhh1q1bt2LFiqKiIize5XI5X6NBh/XuLQwKeigoaOzYsU1NTSUlJQzDhIWFeXt7ozu5oqKpqQl9NG3Fqjwezz5DobER3TYCAS4HYfFg69ItFpTQ9fBAIonYEIsd4kUi1O/j4yNkmIceeuimaxCJvHU6UUwM3hXxeLyhQ4d+9dVXNTU1FRUV3jxeqMmEXi4hgVxRdZsuQACF1NRUXIKamZnpMhZkEM7pcuTloSWOOB3t2jVc1UG2AcVeIBoN9nHuxTB79uwhj6gUCgdMnLhryhT8b0KhcO7cuUFBQRs2bHj66afxP3p4eAwePHjGjBlKpVIoFK5fv37z5s379+9nR9kxDNO/f/9nn33W57otE99oHB8WNmbnTnN4+E0ZYZs6mWXDZDK1FRR4aDT8mJgOfk4hISEh7u5oe3k9dywUCpcsWYK/qggIWD9v3mZ///0//nji3Dnna+DxeGvWrNm8evWer7/een1UAm73nTVrFhIfuO6Nw+qjuhrVHVqtKLjuNKD0xpYD+8mSAP3hulit6NNzPbZBnSwfH0+4M8vL0be7uaGb8/q383g8uVw+ePBg+zE6HRIfDtMN+Hy+r40b56mvtw93FonYuw7R0oK0BZ+PphvQQnbYYV2rJU/Nxq/u5oYCgw51Gzeuoa4OhQ0jIjqEZIVCoVKpVAoEqKKKz0fqhyg+8IybXr2o9bzAbZCampqenn727FmX0R/gvN61aGykPiDxeDk8QJu4Na+rQ6sTx5Ap1svRaUKnUCh89NFHx997b9nZs2qx2L9fP6VS6aghgoKCXn/99eWPPqqqrlb7+vr7+/fu3fsmj1SrrWo+IkIUG0udj8IwwqYmz5Zg3gg0AAAgAElEQVQWtAo5m0kaDGgDJpUS1iibm0CQj8/ra9cu5/NVKpVarXa+Bh+tdtmsWc9PmlQsEhnM5uDgYH9//xv596wstAkk+qvitb2uDj1f3N25LQmCadPFQX+48lYsKwvde7QJLFevokd4bCyhXKu6GukDPz+UfYiJIZth4MiKu3uH6AUh9RMQIPLz8/X1bWhosGJTEJz0YRhqsRge62y1InHdty/hGGwRKJGgwCBxcjR2Xw4IoNa6V1ejBSUkhFyQi8UZzYEHuG2Sk5PT09Nd6ZkN8Y9uE/3FOxylklxXfu0aCn7IZOTAiWNqhjZeW6cTVVZGJSVF0c6Qmyvh8aImTIgiLaGeAoG7REIe3cJSXY22SX5+5FUuJwddGPEMeXl2NwGpVIIWWgQ5M2U0eiYk9HdeBq9eRWegFd1rNGiJtmXGqTs0m28CN1B/6qLk5aGHNK0opLQUfYCioggWuSUlSNX6+6O4ZWQkuegSW3XxeFzjiwwGe+onLMzd3T0wMPDq1ast2Pa4sBCd4Warj5uorES3vV5Pnm2L8zJCIdIfxBEtbDcQcTCVyYT61Pl8ZJRCK+e+dAmpE9q7Mxqp7xq4GRz2OHPmjMs8tvEbgXKWroJT2N9OcTGqXaANh8PRTRz+pIHb4mizbS0WrrwP63cQG0vcv/m2tDS3tLTShrdh9Hq0Enp4kF/iyhW7HRHxpXU6rgUWx40qK3HlHGEPVl5uH71LXP9bW+2xYYOBWheCewJscGw/QH+4IkVFKAAQG0vOLNTUoMILYq24VotEq5+fXXzQLAJzctAzOCaGy2EXjzjq1w8bikRHR58/fz4nJwd9cI1G6lBKHBTFlmL+/uS1w1aAwlVQlp3NFZjB33596Db5yi0Wrm7bggLqlwAn8KOanYXbrXEZFeU6EKOzVVXo8entTa5INZvt8dfoaOoKVl+PwgPcs23d3PD6Rhv/hpZQYny3oMBPIjHweMU290UyFgsqznNzIyuM3Fykroh2RGxFC22Bxet8URHSFsSmSNwvqVSSB7jg4aa+vuhVIiLI8/9aWtBl3Mb8F9AfLgdrFENUD3jos78/IaBnNKIPZVgYunNsFZ23iEnSUif45uTzGdvUXEz//v2DgoLOHj2KhLmfH/XZj+vF3NxQXJEYcsSDK/F0PdpL83jUwE9REXqbtMAJ1hatrdSkFZvVAn5jCGT/9QK3bg27k4P4RxdxtyP8Ihobkf6QSqmRCZuHKdcKhr0cvbyow+VtHurUVUKtRtpFqSSHV4uLGY2m98CBIaGh//rXv1gPRvI6Q1zHsM0aseSlthZJB6mUq6LFYEBrrFSK9JlzerqlBUXH/f2pZygsRMKirg6twDSr6Lw8xttbwREdvw7oD9dCrUb3nkLhOHv2Bi0t9k8PMTFRXIz0fkMDum1oHR+40ZyYFulggXzz7REeHv7RypWzR47kuqtxSamXF9IuxCtUqZA4aGtDkQ9iYPDSJfTStIKpsjL0vTweNWZYVob0Ga0iFYdG9Hqq9AHoLiCukYI5e/as48MP6HLodOjxLBJR7/GSErSGcHTU6/VIoEilVDsl7KFOEx/YLYO4wWODu717e4eGDhs27MKFC1VVVYTDcnORQoqNJUQXKivRGYjNrg0NaH329ORKi+PktdWKbeaJPmzoDPSKFrTwajRoDaSN4fz1V/Tzp0WGbgb0hwuBpSvN6gPHzdzdycK5pARFHdra0OeS5jODdX1AAFc/Kpv17ODyrlYreTy5nx/14d3ejm4MHx904xGPqalB4gCLD2I5GM7scLSKaTT2kxODrrW16L+QEOrChNVPWBj71m7MwgZu1YXrGiEQNosE8Y+uCK4tw111xC1EdTWKjnA4HePKNo4J2NxbFLYohLh9wkXxfn5McLBAIHjyySc/+uijMOcj8ZiVfv0IgzJw0QZxe9ncbC/Jp8km9uS2jDh5jc3K4uq2rahA32gwoMo54v4WRz7a26lncAL0h6tgMnFZfWDparWSs4lVVehTJRCg+4d45+DMSEkJyulw9KNiq1DnrhZs1CEQcN0bhYVIVbS0oG93Vv0NDWjtsFiooRe8LtCkCVZOBgM1I9vYiM7AMboP50T9/LiyqgBnCmb9+vXdPQTC+knjoA7QtSgoQPd4377kvAB+eHt5UfdXrCUBMfBwO1sUjqKQtrYOoQWJRBIZGYnNxG5QWYmuMyKCUDzR2orUA3F72dqK3rtYfIuoQ1kZ+vlYLGTxkZ2NvkRrJqqtRfs3m88JNTVTXo6UU3g4Vk63o9FBf7gKWVlc9VA4oBcXR360q9WoBFqrpQYncGZEKuWK7NXUoOhicHDHinRcLC0UIvFBs/rA5WC4YstZ9Ws0KDckElErUvHwvJAQcjE8Vj88HjXo2t6OpJWnJ7UoBM/H8fCgijOAk4ULF7pAFarjxaempnbqtQD2WpwbMcjychQDoOUFWlrQE1oq5Wp4KShACx1tQqdWy9XSjxtSGIacl8F5DQ4rJkxdHdoKBgYSNjk4MEP0IW1vR+un1YoWWFriGG8ym5vtAWDnw3BSiVY219SEhJG7O3p80BbJxkZ0/b17/6YdGugPl4Djo48LO7Ra8n3V0oK+6ueH6r2JgQe2nfV6MwsZXNYaENBRGrP3RkiISST697//Tch3VlQg3Y3rKpxVv1aLEh8eHmhZoVl92GZeo/9oJS8SSQebspvIysIe8OSvqtX20Y5Q9vE/gB/Y3ToFc+DAAfwHSL50OXC7Sp8+5LxAWxtahcRirvgrrmyLiiIbAmEXVG9v6g4kPx+FFmjzsXFLHXc9Zoste+7riwpXnbl8GYkGonzJz0fLLM2kBKNWI3Gg15Mtl9j3TiyqwyU1cjk1M87GZmQyx+j47dRIgf5wCWi9WDjmVl+PVLPzfWUyIfERGIi0bVQUWfWzDoAc4ho/4729CdL46lX7UMRevbRa7Y4dOw4ePHjTATU1KLxhMqHLcF47cGSCz0c3BjHvg63M5HKyKjcY0IV5eKA7k/bMwNKNJvwNBvTDsVqpVijA7THF5l195syZ9PR0phuiUqnYK3cZL1cXoa0NrWNyObWwvagIrUIcVst4fF1gINUQ6MoVruhycbHd74DYGYetmGJiuGazGQxcY1YuXULXT8yMYN3DbfWh0aCngMWCTk6bbUtreMRNkb16oX1gRAT5DVosSGDdMvtDAvSHSxAXR/5kNDWhbYGPDzkmVlSEPrVqNdmCxvHz3bcv1QtEr0fH3Fwu3tTU9Oqrr77z17+2Njd3sPrQ6XRms9n+l8ZG9NEXCJoY5tVNm9555x08GbLjWGfslEokK4tq9YErvSUSroYX29xLqnTDZ+Dx0LoG8+d6dhXq4sWL2T9PnTq1U68FuJm8PLQ60ZYI7ONJqwxjY8C0wMMtjaQrK5F8CQ8nr5A49swdnLBct/ogBkgKCtAaRXy0Y58xDi8lNv0tEqHDnDd4ra236LbFUY2mJnJmHJOVhf7fr1+HZ9CNMGGHVd0B0B8uAbHeCu/+5XJy1LG0FOUUtFpy4AGTk4M+38HBVC8Qkwnd/AJBh7JWlUr17eHDH3/++aELF0w3Zz2uXbuGZ0iil8bBCbFYZbV+++23H3/8MZ5YbT+0sND+B1rGEcckaaEL/O245pRj1xITQ846sdsmLy9axhfi8L+JhQsXdtNG3PT0dLbyNCUlBX7vXQiVisvvp6IC3eO0yjB2jgTHfNf8fCRfaOKjoQFdAE0BVFWhA265e8nKorqJVFTYy+qdxU1VFVpCObyU2KZCgQAFMJwXMTx/lMPCFXcy43pY2v4zL8+elyE9g5S4U5KuvUB/uC7Z2dR6K5z1aG8nW9BgqqrQjefnR66rwOTmoie0U/Ql3t9//YIFQxITj50/r9PpLBaLRqNpaGhoa2s7cuTIk08+OTQ1NTQhIXTatNc+/tigVMbHx69fv37IkCHHjh3T6XQ3SrU5Ni45OeilaS6lJSVoV9HWhmrFiWkj7l0LPoPBgEKmHOMhgN/CtGnT8JN7w4YNTPdBpVKxM0UZ2xToTr0c4GZMJmrLxu34BWRnc01asHmFoa8SUyc6HTrA358cOGloQIsMR72qo5NpfDwhgM1mRpzFE56cd3O9BQEcvvX2Jmem8JQJWtKkogJdmE6Htn809VZejmIbtunBhK8WFChtm0+O/QbMn+vGcO3DrlxBspe4LWhqsn92hUJqxhR/9L292c+3xWLRarV4zLR9QGJubpVKdVajGRcbKxWLNRpNQUFBr169Qjw9hSrV8MGDhz/1lG2DYVyzZs3HH3/MnvvMmTPxkZF/mD59UHR07IMP4kHPw23cVKrd1oaCExQDY3Rj3Jw3MZlMZrMZna2iAgmXtjZcd6LX6zUajVQqvTH4sbER7Vo4LIpVKnR+bAHkzPW5BmBC9VuZNm3a+vXr09PT2Y6Y7pV5WbRoUXe57B6CMjmZbOeDPUwdpnNTa79o8qWqyl45R9yimM1cFRu4mFQmo8ZuMVevoiPj4wm1ZS0t6PqJPmZNTejBzz37k7XiEIvJO6isLPQWaFaNbLctreUQH9PQgH7CxAAMjjxxeGTbgPiHK4JjYsT7qq3Nbi2My0KJ4IZViYRNqebk5MyZM+ceG2lpaVevXsU+Y+eamrZ88klNTc3333//8MMPT5kyZdSoUd99/rmj1YfRaMSdcomJiT4+PhMnTrx88OC3mzcvnzFj3MyZIc7XgMc6m0xMVJRJKs3Jydm3b9+mTZsyMjLQ+DocGrl27Up7+6lz524kaxjms88+mzt3bn1ODrpzzGZGoTDKZHv27ElOTh4yZEhCQsLatWtRfYlGY2+jpz1IamvRHW40op+P8/1jNML8l/8aVnZ0lxBIWloam3lRKpU4hQR0IYjRTb3e3m3L0fCCK9sSEsiVc3iLQmyFdaxIJTak4NGbHC11jl0n4eGE+G57O1rDfXwISzRuJOb2UmKjF7QhWUVF6EdES1pVV6PIjUBAbTnEzwiVCr1HmvyqrmYCAoJvFTyG+IfLUVKC8oJEqw+rFX3yvLxQ0Ozmig29Xl9WVubr6yvAN49I5N6vH07oXbhwYfny5dXV1ePGjcMW1G++8sqGZ5/tlZDgq9c3NDRkZmbu3LkzJSXlsYkT3aqqYhUKJjrayDAVRUWhoaEymWzt2rVvvPGGSCRasWKFu8nkxufbhys63HhYpoT6+AhLSxmRyBoYmJmXt3r16kuXLrHHxMbGbnz11b4CQYuv784PPywvL9+4cWOQ7Q5pb28vLy+vq6pqLi72s6VLTb6+O7Zt27hx48yZMydMmHDixIkdO3Yk9e8/xs8P3Ta0ohA8PEIkQkuPc1CxvR0FbDnq2AEXCoFs2LDBUXzs27evs68IuA2wVYZAwGW2UVKClqC4OKp8wRWptAAnrrgkVmxYLOir3K+ONznVttwKUd9kZyNx46wwDAa7+AgL47L6qKlB65jVSh4Rih3co6LIVYM6HTpAKqW2HOJNLLY7IwZg2tvtJTXBwbe8wSH+4Vrg2bZhYeSYIZ552NyMPnwOn8vKysonn3xy7NixgwYNSho6NOnpp5NmzVry17+2tLSUlJS89tprDMPs2rVr69atW7ZseeHJJ81tbSbbjBh3d/e6urrly5enpqa++eab9/n7D4mO9rznHsbD4/Lly48//nhubi52+pPL5UKh0N1iqa6uNrS0OHeCoePT0nIzMhg3N6uv7zdnzsyZM0er1S5ZsuTYsWN5eXlvvvlmbm6upqCA6dPH4ONTV1eXmJjod/3ubW1trSgpQcEJqRTdmcHBGRkZGzdufPHFF5cuXZqUlDRp0qTg4GBdbi5SD7SIa309EvVSKdnjz2RCyVoej11Zuvjjs2vSXUIgGzZsWL9+PfvXtWvXwq+7e4DnT3F026pUaJEMDyc3/eFuUpmMukXB0WVaRSq2mQ4N5ZoN3tRkd1sOIkUXrlwhl6NaLOipbzKhxZNWkMHuoHDdvbPCuHYNyQvi2Fu8xOENKofdEe7WwZEV4k84JwdtfW2xn1tOqICdXDemY/2BVovCbr17kzN2KhW6bfDgxJvTCnK5/IEHHpBKpfEBAYmhoUyfPmX19SNGjJDJZHv37i0oKFi9evXAgQPRsOvGxrkjRsx99FH86ZTL5TExMSaTaebMmdLaWrRvCArC94aHjZv6aevrGb3ebLFY/P2dO2483Nw8RKJWs5nx9KwTiT7//PNx48a99tprXjaZYjKZrqnV6DgvLyYkRFNc3NDQMGrUKPH1vOm/jh49euJEbEQEyrxERmo0GtznWV1dnZmZqdfr9+zZI7FY+kdGUktW9Xr005PJyJkpXCtuNqOiE+LIKMCFQiBLlixx9CnZu3cvGJ52D4qL0RLXrx+18qC+Ht2/QUHUsoYrV9BjlRa9wP20tIpUPBs8Opqr4QV7SdMsi65eRdIhMZGQFcKzuzl6edimQoEAiQNnL0c8AqxXL2rquagIxV1odW+YrCy7gztxi4u7ha9ndiD+0WOwWu0OfcSPdX09irlhj1EnCxqpVDpv3rxdy5YtSUsb9/DD4yZPnjdvXoztDmxtbQ0JCUnAYhz7oDvsDHg2Bg8eHCaR2Ac7XVf0bm5uEomkkO2hvXYNPd35fHTfXi9HP3ny5J49e7AdiFttrcTNrbC6mgkLa2tr0+l0ISEhnrZbyGQyHThwYNOWLbHh4b0c1IP79SVGVVb26a5dAb6+9p0HugsKzp8/v2DBgpqamlmzZs2ZM0dTW7vq6afDR40i//TMZvvo3dZWckYzJ8e+6aE16wLdJwSSlpYWGhpKK8t3FB9KpRLER7ehqgqtQhyzbVtbUeaFo/YLz0ChbVHYpjli4ESlstdzcIgPo9HuVkLMXJSW2rttnZ02ysqQrvL35+pG1OvtEW6lkhzeyM52rOoj9wy2tnaIjhP8JJ2HbGCqqtAzwqGiBe+QOfpfYDF1FS5fphoMY4MdPp9sQYMpK0OfvICADlt/qVSam5t76NChlro69OEjjc8VtLfzqqtRtZRDtM3b29vX1zc3N9dgMKB8YXW1m4+Pv7+/WSSyWCy2VKbh6NGjly9fRgcUFXlLpb4+PrkNDQaDQS6X+/v7//jjj8eOHcvIyFi0aNFrr77q6+PDhhPxyX/55ZeWlpbW1tbN777r5eX19EMPNbS06GzNKSqVSiAQpKSkbN26NScnJ+v77w+98caA8eOp3bZ4ug0ebO1ci371KvrhxMfjnCsup+2aG/fuArYQTU9Pv/teIGxJKfE3mJaW5ig+1q5dC+Kje9DcjBQAR7ctzp9yTOjknoHS0ICer7SmOTyfMiCAywrMbLa3+xKHgNbYUuehoQSzJTy211ZRwXXyoiK0yNM0CofLCH4Jnc4+/pNYF4IFik5HdWTAM2J69fpN818g/9KNubGA4vkCRB9Psxl9btzd0ceaw+qjsREd4LQiP/jgg999992GDRs+2b49Njxc5OODA4MymWzp0qXoCIulqbKyXSSS3JwvFAqFYrHYYrFYscu7SMTj8wV+fpU//VRTUyOXy3/++eeMjIw5c+a4q9VMW5uQxxP7+KDjrVYvL6/HHntsxYoV8+bNYximf3T01qVL67y9t27dik/u4+MzYsSIt956K8/mbSwSCt+cM8fUp8+HX399+fLlxMTE6OhokUi0f//+qKgoWWsruq+INzampARFZZqbyWMni4rQtiY+vsNtCfrjf2Hq1KlYfGzYsGHt2rV3X3zs3bu3w5dUKtXixYsdfcag4LTbgGdUOfgF/GYP9dJSdJtHR3PNQPH1Jc/O1WjQt8vlt3DjyM6m+qhqNPb5Wc5LNNY9HHELR7NET0/yFeLJwLRu28ZGVA9ry1wTFkBMZSX6+dCsRNra7GbTN2u7Wy6SoD9cAVVZmZKWWSguRh96qfQWVh9SKbEdNywsbOuHH361des/T57MxO3ytqqi6dOnBwQEtOt0Eb6+fIGA53RXy2SyhIQEsVjsVlGBJL/ZzERHDxo0aPPmzdOmTZNIJA0NDWPHjp2YnMyzzX+RJSYmJCai493ceDzexIkThw0bVlRUFGQ09hGJhAMGfP3tt76+vt622KZAIHj66adlMtkXu3ePHDLk6QkTfKOjW2WyyZMnZ2dn6/X66Ojo2bNnr169uqq8fNawYf0GDKirrj779dffffed2Wz+8MMPw9g5UrgsxmwmT24sLUX3f0yMY+Ck29l3dkGUSuXdrwJh+1mcUyoqlSotLY39zULOpbtw9uxZ9JvKyeHSFlh8cHioV1ejZTAkhDofGwdOiCWZra1I+kilt9AH2dnoPPfcQ0jgttrO4O5OSJ3j0LVIdAurj9JSlHwRiciWCuXlSDr060fOqrS02H1Og4Op42/q6lB4Riolh44sFvuQUaeLvOVSCfqje6NUKlUqVYVAoCQGzVQqpEzFYmrIEVt9cE6G9G1omDt+/NzFiwlZz8LC1+fObQ0OljnVlAgEgpdeeokpLeW1t6MHvM3mfNCgQY8//jjqg01KSktLGzNwoFStRs/+mBiBTIaOt9WU2F/X19dXo0GP/759GbG4vr5eIBDwr9+9YrF45gMPzExKQvezpycTECBlmFWrVhmNRontRzF37twgX98N69c//e9/42/x8PAYPHjwjBkzbjztamvRT8DNDSl354YXlQodQBzaBHS3EEhmZibuZ1m0aFEHbZGZmfn444/jP6ekpKxbtw6CW12fG8+27Gz08KM1teHwcHs7M2AA+asaDbrTaQO0ceaCZvWB5+KKxbfots3PRyIjIYHQNNtus/qQSAjaCFsNWa3UybSYykr0FmjXgE1gg4PJi1h7O9I3bm4otEPLW+HZ5kIhVQMVFdm7cpyeQThVzQHoD1fQH2dzclLHjiUbeQmFVGGOK7F5PCQ+aAVHePxB374E8ZGVxej1fvfeSwvZCXFHjF6PbgxbRZVEIlmxYsXLL78skUh4zc3o7uLx2KCf3VaVpbYWvYXevXHepONousZGJMllMnTl158WQhv2PwsEj0ZHj//wwzJvb7Va7e/vr1QqsTS5cYaqKrTjsVgIO4/aWvTVkBDnOvmzZ8+Sf1bAb0GpVKampqbb+L1DICqVCiuMlJQURw+xDjmXtWvXwmzb7kVmRsbC4cOpIyRx6qG1ldxRwjpqcNikclh94F5ckwl9laPbFpu406ycc3KogZnCQrQ3i4qiDgfFkYn6erQH69uX8AbxeDk/P2rmvagI/d/bm5y1wc+IggL0EImOJrf8VFSgYwICiJWFqgsXuLMwUH/qChDCXDodKmtgGPS5JH5ujEb0+bZY0AG0gqOiIhSdCwsjVE6UlqLICrHLC6NWo/9wx43D/cPj8dzd3Xl6PXp1bABPDPrhmdG9e2NloNfra2pqOraZicVcLq62PjHRoEFRUVGpqalRUVE3iQ98Bh8f8oA6tRoFLQMCOGY7QRbmf2fKlCn4D793I0xaWpqzh9iSJUuGDRuGxce0adPKyspAfHQ7VFVVaBWimXHhqo6+fcmzWy0WriFZWF4YDNTp4rgsnWP9xOqnoQGtUcTwQ44tMEM8P54/RetkcTRix2u48yJvNqO0kYcHdYVkDZNoJvHYixI/RIjiCS/yEgk5uV9bix5DnID+cAU6hrksFvv016goah88trIhtePaKS9Hn2/iaEdcqs1xb2D1gEfXEl1E8Uhof39y0A8HHh1a5A0GQ3V1tf2rtn4Z9L3EuIWjuTKtix2rHz8/tDZFRna8+dva0MV7eiLhRSIzM5N8WuA3kpqaivdGv2sjDFvYwWZ5lixZEhoaivtccIft3ayBBe4gKrWaWldeWYnCA6Gh1IZYbPVB7EbB4kCrRft+onZRqewV6xzdtniSA22ESmEhOn+/foTzV1aib5TLuWbXtbSgM+CqC6IAwk7NtHeHZ2yJxVSfMasVLcIWC3WT2dyM5J1QSG5mbmlhyssr8cQMOqA/ujfkBmsc2KDl/LBy1+vR54bWjosVBjEA0NyMYm7e3tTYAK6FFoupTmjFxUiby2TUoF9WVofpShaLBduE3LCQx1OhiTceNlemaXbW6uPaNRQU7ZBYxelYUpsxC0Q+7iBsyAH7xd1x0tPTcYQDl304Kg/86qdPn4ZS0+4IG9Un7wfUarvPGK2sgdvqo6oKPUHlcvKjt74erZDEivUOpXUBAeRtTEUFUhjEhruGBiRcPDxo+58baSOGQfKImJ1hx+oSaWhA1489TImhHdYJLSSEvMk0GJD4wDtM5wtob0fqTSJRdUiaOwH6wxVuwpueiCoVktWBgVTtXFGBbq0+faj1Vg0N6CTEnCge7CSTUetV8dNdJKLORSwuRuENmYxaEnv5MnVyLw6oisX2+QXOc5twKXt9Pdem5+pVpFpwWauzQMHWwrRXx5EV4M6xcOFCHHtYv379HRd2KpVqyZIlDMMMGDBApVI5Kg/c5AJhj+4LqxoJyTut1l73QKs8uHoVbZNoVR1NTfbhc8TKOXayLocbB25pkcvJGqK+Hi1TffoQtme4G4Wj2BOHt3HdCS36gk1gY2LImXf8EjhwQrOoLy1FqZM+fcjqzWq116bQlllc1BIZiaUhh74H/dG9SU5OvmkTcO0a+mT7+lLFR20tiknK5dTYw7Vr6NPp6UmIy2EPcqGQy50X5308PMj1XFgbcZTEXr6M7iunajIPD4/o6GikfsxmdGPQTAZxbCYggCqtiouRuMHREeedB07H0lYlW9Iq/euv8R9h03ynmDZt2u9UfLp48WLsoXfx4kVH5ZGSklJWVga/QddY+jrKVqMRbRK8vbnqHjQatIMiVo3g4Wq9epHlhcFw625boxGtkzIZWUNotWgVIp6/vd0+Xq5vXy6f5YICtAzK5eTodVUV2lzRRoCx47tp4WG8Sjc2Us1O8CJvMiF5R1Qnubn2zLhUCv23PWUEzIYNG1IHDUKfDHrhgr2TytOTemfi4c4eHuROeuxyxhEbwJOZaEOZa9OfTRoAACAASURBVGtRUJSjl72w0N6p64RYLP7rH//YbvNoRzsPYthTr+dyoMeBH4MBvQTRPxhvGhISqHuCoiKmufns9VIbdvkD/nf27dtXUVFxZ1UI29jSoXOK5u2B+tgrKoJvY2gn0KWWPpVKlZmZeeN3mpWF9AEtQFtVhTZgtKZ6k8k+fI4oL25nA2a1osyOWEwuvMAVnbTzX72KJAjH8BrWhNRh0gW5l5g23QbHLTjK/mpr0X9eXtRVtLwcRXc8PMj6DPfi+vgwAQGs4udYKkF/dG+USmVKSsqZM2eQ0szN5epEx9227u5Ulx58b9DOUFiIzhAbS+1Er6xEj3ZabANLHz4fffSJD3iVyj77gJjObGoS1NYK3N3R9RNvPDy1UiKhvruaGnRzYn9iZ9muUqGgaEQEOaeDA5JaLRMQkHnxIv4H2D3fQZQ27tTZMjMz33nnnYvXf1MsrLcH3pZlZmZWVlbiwCHbgjtt2jRIynQLHD8wBw4csN+Ply5xFV02NqI7nWP4XHY2Cj/Qvj0ry95tyxGcwEZnRDMSPDmWdv6SEhR64R4fg+tS/f3JayBOjhN9zNiXwCNCaWV/OPPO0RBUU4MuQCAg7zCx3RSPhy+A9SngWCpBf3R7UlNTsf7I/PXX1FmzyAe1tyNtwTHXkR0uHxtL6GXHo5U43Hmxyw2fjwQE0eCvqAjdfjRpX1GB0ka0sUb427280Jlpt9bly+j/3LMb3N2RuHG+devq0KsTO30wZWXo7dvazNiIIuySuyCZmZmsyWkHNm7cWFxcvGHDBsdEjLMGYluCga4P3nrh3zsKgchkKPxA8wLBy4ivL7VuA8d3aRWpRUVoFY2O5uq2zc5GCyntDDk5KPZA/GptLVqjiBUhjhdw7RpaIYnXj0s+3dyoPmx4iEzv3mTtgmMnRUVcG9TGRiSAcO7GeZGvq0PSpK0NqSvbV9m6YI6lEvRHt2fq1KnY2PFsbW0qzQYnNxfdmfHx1ORCbi66c+LiCOGNxkZ7tRRNNeNGLB4PfXCdv91ksvuMEUsucEK0pgbJC2K9qsmE7gpvb/QHWkwVV2PFx5NruZubUW7Fywtdm/Ot29qK5IVcTi1Vw9rLZhHrOJmMfDDQebCzXVisViuPx/P391er1S+++KKz2khNTVUoFPgPd/16gf+VqVOn4t+4SqU6sHNn6nPPMQMHkg/FsQdiWZujTVl8PNlJDAceQkK4rJDz89HTNzGRvMZiC9TrMyxv4pptNjhp/NZNxzQ2oqwHrWw/L8++wnMEfnx9qS/R2op+Ajj4TYzu4KpVPp8cJMZ1hzweSv1fD2DjrRq3pw7oD9dJwaQfOrTwL3/hctEhNrLjuGJbG4p8OH+w8OAljmJvHPTDophY8YSrpWixDYsF3ZleXlTRjVt5sYkqkeJipDDi4siRFYPBLj54PELVC57s4OFBrSbDHqzYXpDPZ3tE4XHV1WD7bKdOncr+mrCXv1qtdhQcycnJ8OtzDVJTU9kQSPqxY1Nmz07lHg9OW0NwNyzNLQkbJXNM1r1eHIaWUOIaW1pqr3l3XiH1Ni8id3euglZsQuruTk0M4RWelhjC0sHTk6pdcHQcbyCJNbk6nb3xsHdvwjKOA0tSKfrv+o/odoo/QH+4CAsXLnz88cc71mE5Pp779aOOnsdTp6OjCcEJkwl9LjnSgXjyEMNQO8FwUpPWx4XXBY6ijbIy9BJtbWjhIN4YuNg7PJxcNcI2A9tGzBAOwNVkHNniykq0q7CVymdmZrLba4jSdzVSU1PXrl2bmpo6bNgw50F3oDlcEqVSyYZAUA3+Rx+ljhhBOA4PzqQlJvAATpqbIi6b8/GhZn5xSSZ2BCCuQngPQ9uA5eejiAvH5DyjEckLsZha9FpSglb4mBhyYqi93e44QNNeuKjWZELnp9W9lpejw4gT1M1mlHWSy+3tuNdhm6K54x/Qf+s6+wBCK7xKZX8802qacCtaRATZQzAnBwlq2uOZNVGl+Zjhkc2+vtSMI14XOIZSarXoP5rVB9YHHEnToiJ0b+NmMOedAb7raBHL+nr7SOvrr37gwAH8lZSUFHiYdTWwzsB5MT6fP3Xq1EWLFpWVlZ0+fXrhwoXw+3J5C11cREzwAsFNebSajJYWtLOnVXSyGzD6eE60TNXUUH26rl1DD29fX3JyOT8fXVu/ftS0OBYHeEgWMTGEC+fDwqiJIbaqj0ZuLoqd0HzM2JYWiYSswC5fRm8ceyJch7UzvuVAA9AfLgKeqnXmzJkbboDY5Yaj2LuyEqkThYKsHlgLc5pBXmkpirzR5kZii0CZjLpv4F4X8Hg5oxE9/om3Fg760aqxsLQymdBbIIY9sfkxzaKnvR3d2DyeY1yHjSg6DjADuhplZWUlJSXr1q2DX1NPQKlUOv6i09PTb7JDxbf59YrIjmCzY6mU6keAfbQ4NmD19WgVDQoi+y1hFzKaE4lKZZ+uReu5Yx2JYmJoXYFohff2pkaXc3PREhoXR9U3BQVIOkRGUjeoZWXoXQgE5LqZS5fQCoytqB0q/9gE6C3vQdAfLhoCaWlBmRcODxm1Gt05vXuThXlZGVc6E6v+hgbq+bFF4M0e6jdRVITWhdhY8rrQ2oounsdDJyfuKnDdhpsbNWmqUqH7CosP57BkZSW6Z8LDqXd+cTHaeTjEdbCNJgQ/AKDLLn2s4629Sa28HN3mHEZbWVlocaBFQHFwgrZGsYXttKJOdpIDMXaCpUNvulEHW7Larx95mcLzX7y9qbEZPD2UYw0vKUHhmbAw6hivqip0gNVK6Go0GtFPz9vb2UWercS6HV9B0B+uw7p16+xByHXr0Eff25tacKTRoA+fnx85eFBXh3KWSiU1IodVv7c32eQUzyYQiaivXlLCZbaBG17wdDqajWlODlL0tNgJ7gTT69HS4/wSOGsTGEi983Fcx9+f3dNkZmZC8AMAuiZKpXLdunWOEgRNHLx40Z4WoU2ny8qiDr7Hz37skUrrtm1rQ8fI5beInRCrLvAETS8vroYXXNVBLMtjPV5p4obNvEdEUMv+KirQIqxUUpdB/BTA8+c6dDWazfbrb2np4CbCTjy4zaUS9IfroFQq7aM0Pvgg/fRpak0Tjgr6+JD1Ae5H9fOjjperqUFPaA4HYjwhpV8/8q3b2Ig+935+1G7e4mL0fx8fauQGN9nTgqI44Yorap31E77zObI2NTXoCm9ux4XgBwB0fQnC7raRBJk7V2W1UsdQ4OQyrSK1rg6JD6WSWlRhMqFVyNOTGt/Fa1RICLlqHhtF9qPXnBYW2qs6iGkR3EvM51OrOvDsPY7xotjkNDCQusg3NiKBYjaTt3CFhUjW4Pl8N28R8cQD7DJ8OyYFoD9cLhRp63fa8OWX5LGQbMcpUThbrShwwjEczmBAwQMOH7P8fBR4iI4mxzw1GvvsA1oXPpYOUim1aiQnBymk2Fjyjd3aap9JHR1NXjtyc7myQjg0IpE4Gtiz09uVSuW+ffvI3wgAQKfS4fZUqdVpf/4zoRyVbQmMiSFXdOp09rm1tKp5qxUVznOMyC4sRAtR377UujrcbEKjqgotRH5+1MhEfr7dpp14/RoN2h9yXH9jI3qDHF4geASY1YpewnkLh4PTra1Ift28RWQNePCsaeY2AP3hcvuA997DDtNLlizpePtZrSjqSJtNwJoH0+4NXIyNO2KIOdGyMvTpj4qi2qRiMw+a+KirQ6rfzY1LnbS0UOs2zGa7E0lkJLWdh8Oip60NXb9I5Pj22VwmiA8A6OIolcrTp087RkHWr1/fcQ2srESLTHg4OTFhMtk3YLQRWqzFO20ZKStDyV/agBWVym4EQtw+MdcHuHh5UdM6BQWoco4YlmBz3z4+1OvXaJA86tWLen6tFkXHeTxy6qe8HC2z7e3o1W8OIS9ZsgQvlSkpKbefpBasWrXqNg8FugVeXl5xcXH79+9vbm4+c+YMj8djM6OoV4rHo5ZN4JnUSUnUhpecHHs1NTGxUluLKqoUCmoxNhY3NHdkXJKC29yJF1BdbW/TpxWFYBOesDDytoOthKfd+Xhso4MB4oYNG15//XX8561bt8ZzDN4DAKAL4OXlNW7cOK1Wm5OTg//lzJkz+/fv12q1aBlsaEBPUFq7Cl6j+HyuCdhXrnBZvOM1KiSEHLrAkQmFghrYaGtDi5iPDzU1gytqg4PJkyKsVrTCcwRmWlvtdYG0qhGdDh3A56MzOIuP6mr0FpzGm6tUqrlz5x47dgzXnG7bto25bUB/uCDBwcE8Hg+r0TM2UB92VhaSrklJ5O8pK0M3J83EButuHLQk7hu0WvtsBWJFKpuX6d+frC0MBvS5x4Mlia1i+PweHlz2yS0t1Dsfvzva0EtcjIabja+//bS0NLaLjDYxFQCArrkB8/b2Zn3J8E5sf3q6tqIiZcQILkcAg4G6RuGqDqORGTCA/NXGRiQvAgPJiQ/s00XrxWVsB1y5Qp09zoob2vlxYEYgoIonoxFdgIfHLdQJFh/OaRdcEcLno7fgEPnIzMwcP348zlAvWrRo5cqVzG8B9IdrkpKSwkoQlUq1/4svtBpNysyZ5LxJQwP6bAUHU+uVyspQ0LJvX3I9VHv7LaqxWHFD6wTDk5kcHv83YTSiAzw9qWkjXOzt50cuWdVq0brg5UXVRni83PVeXyzn2bTL1q1bQXwAQDfCy8srxYbKBv7HZq32THb2/hMncnNzPT09gztUoONmVOIALExeHopP9O9PXkJ1OrTF8vWlJj6uXEGRVw4rkV9/Rcsjhx1ieTkK/dIK57m3l1jcSCTUC2hrs8/mjYkhT+EoKEBfDQjAa6xKpdq5c+fixYt37tzJrpO3dBtzhme1Wn/r9wDdhczMzMcff7yDR2TH5JzBgD6avXpRa05rauzqhBa0/PVXdE/S0jr19ajgKySEqxZdo0Hig1Y1cvEiWhRod2ZdHRIQffqQ70yzGV2eTEbdVVRUoDdoe3cqlcpxPmpKSgrUfABAt0alUi1evNh5JDI7DAj9ISICrSHh4dTMSEEBWqPi4qiVZxcvouWLtshcvYqCxwMHUq1ELl/mSus0NyP14+tLjf7m56Pob1ISuSIVL6FCIbXfp60NbfBw7ts5/IzrbQ0GJjxcpddnZmZWVlbiiafUZ8ptA/rDxbF3w1/fBBAmYly8iHQ3TRdrNOij36cPV0NKWxuKSdKcxHJy0J1DizqWliIBER1NbdO/fBmVZdB0vUaD7j0/P6p4unSJq+SlpQWpfi+vzMbGG7ZFNhYtWgRWHwDgGnTYWnRA6e/PCASp992Hh6VV4inzLE1NqrIyFPq9XjpWUVFx0wFaraq+nlpYZjajslaRiOHzHVeY2wHV0lqtKADM51PPbzKhlxCLcdrIues1GGfMnUzG7EcajWiLKBQqHPJKN/0E6uoYkymzuPjMzz93+PaFCxf+FzEPR0B/uD4o/7J/P6tYWdA8ULk8NSEh+dFHySkGgwE9/uVyqtVHYSEq9r7nHmpi5cIFVA9Fa6ipqUFBRY7QSG6uXdwQM7JGI5IXMhn1/Hhb0L+/s6hXqVQVFRVnv/46MyvrTFZWB3E2derU22leBwCge4GHdJ49e5amRQAO8Kp4B1dI0B89S4Wwk4GI4I+UUqnEyVGlQKAICsLlTo6fNnvqtKYGSWPb6CPyZxHXijvEHhxfuiI/H4kP20xF9t9v0t0NDaqKCqR+BIKOGw58NuzRbtsWEC7AYAj28WF3LewZHFPCHd77/xJIBACge4E3Iey6VFlZif/g+I8dVq07iJJdsiwWNnjcYR1DK63B4Li7Iyx0Wq1j5lpBs228mY4xHs63qVQqFQqF46i/OwXojx4q/ysqKpxzoj0NFAG6ngaGIlMAAG7Jf5NDASiA/ujp8l+lUp09e7bDTYJFtOOGAP/hd9oK3PIuJSQ1lcoOSZmOxxiNjFhM2w1g2fHfXy4AAADwvwH6A/jvuWUqBwAAAACIgP4Afl9MJlNjY6NMJpPSht0DAAAAPQ+S1yQA3DkaGhp2794tl8sTExNbWloGDBjgS3M5AwAAAHoMoD+A3xedTvevf/2rvLw8Li6uubl52rRpc+bM6eyLAgAAADoZmH8L/L54eXkNHTrUYrGcO3cuPz9/z549R48e7eyLAgAAADoZmP8C/L4IhUKxWHzlyhW1Wm1zHG0pLCwMDw8PoU1jAQAA6Nm0t7c3NjZqtVp3d3c+zbW9+wP6A/h9EQgEUqm0qqrq119/tQ0TsGq12oqKisjIyMDAwM6+OgAAgC6EyWTSarWXL19+//33MzIyhg8f7u7uzrgoLiusgK6Dl5fXfffdJ7s+09loNP7666+bNm26ePFiZ18aAABAF6K6unr79u0vv/zy0aNH3dzcBLSRci4B6A/gd0csFoeGhrLRDj6fL5FITp48uWXLlry8vM6+OgAAgC5Be3v7zz//vHv37vLy8t69ew8cONDb25txXUB/AHcDqVQae31KHI/Hk8vlcXFxp06d2rFjB0gQAAAAhmFKSkoyMjI0Gg2fz4+NjR09ejTj0kD/LXA3cHd3j4iIwH9ub2/X6XQPP/yw2Wz+7rvvGIZ55plnYmJiOvsaAQAAOg2LxZKfn//TTz8xDOPp6RkTE+PyRfoQ/wDuXhUq+9fm5uaCgoKnnnoqKirqu+++gygIAAA9HK1WW1ZWhoMfUVFRPWFAFegP4G4gkUjCwsLYv7a2tubn5/fq1Wv+/PkKheLo0aNffPEFSBAAAHosJSUleCa5p6dnamrq8OHDGVcH9AdwNxCLxcHBwVKplM/n43ayhoaGH374YeDAgc8884xSqTx+/Hh6enp9fX1nXykAAMDdxmQy5eXlnTx5kmGYsLCwIUOGMD0A0B/AXUIgEHh6ekql0r59++Jg46lTpxoaGsaPH//UU095e3tnZGR8/fXXIEEAAOhp1NfXFxYW4vbAkJCQpKQkpgcA+gO4S+DIh0wmu/fee3EtiFarPXv2rEwmwxLE3d39s88+O3z4cGtra2dfLAAAwF3CYrFUVVXhBLSnp2doaKhrt92ygP4A7mr8QyQSKRQKXAui0WhOnTrV2toqk8nGjRv32GOP6XS6zz777MiRIyBBAADoIWi12v/85z84+RIeHt4TKk8xoD+Au4RAIPDw8DCbzTweLzk5GRuhFhYW5uTkMAzj4eHxwAMPPPLII83NzVu2bAEJAgBAD6GyshKPpxCJRPHx8T2h8hQD+gO4SwgEAplMZjQa9Xr98OHDcQqmoaHh0KFDra2tQqEwJCRk5syZ48ePr6mp2bJly/fff9/ZlwwAAPD7YrFYmpqaampqGIYJDg4eNGgQ02MA/QHcVcxms9FojIqKiouLY6tQS0tL8aRcLEEeeuihmpqaXbt2wYAYAABcG61We/HixStXrvD5/MDAwOjoaKbHAPoDuEvw+XypVGo2m3U6nZ+f36RJkxyrUPExQqEwPDx8/vz5Dz30UGVlJcyoAwDAtamoqPjll19w5emAAQMSExOZHgPoD+AuIRQKPT09zWZzS0uLTCa77777cAiErULtIEHuv//+kydP7ty5EzpyAQBwSSwWS01NDe68DQkJGTx4MNOTAP0B3FUsFguWGnK5fNy4cVKp1LEKtYMEGTNmDC5T7dRLBgAA+F3QarV5eXnl5eV8Pr93796RkZFMTwL0B3BX/T9MJpNWq8UNL8nJybgRl61CZQ8WCoVRUVHLli17+umng4KCOvXCAQAAft/OF8+eMXCuA6A/gLva/8L+VSgUKhQK3IjrWIXqeEBQUNDAgQM742IBAADuXudLWI/xXHcE9AfQaXh5ebGNuI5VqAAAAD2q8yWkx3iuOwL6A+g0xGJxv379cL97hypUAACAnpN8Ce0xnuuOgP4A7ioCgQAHPDC+vr5Tp04lVqECAAD0hORLeE/yXHcE9AdwV5FIJOHh4exfpVJpUlISbsR1rkIFAABw7eSLUCiMiYnpOZ7rjoD+AO4Sbm5uCQkJf/jDH0aNGuX476wXGbEKFQAAwIWTL/7+/j3K89QRYWdfANBTkEql999/f3x8fId+WplMNmzYsLCwsJycHFyFisMhAAAArp184fP5ERERPbDzBQPxD+DuIRaLiWYeXl5euBEXqlABAOg5yRfPnue57gjoD6Dz8fLyGjVqVEhICFShAgDQc5IvIT3Pc90R0B9A5yMWi+Pj4x944AGoQgUAoOckX3r3PM91R0B/AF3LiwyqUAEAcGFaW1uzsrJw8qUHeq47AvoD6HJeZOCFCgCAq9LS0qJWq3us57ojoD+ArgLrRQZVqAAAuCQWi6WqqiovL6/Heq47AvoD6CqwXmRGo/Hq1avnz5/v7CsCAAC4k2i12v/85z8nT57ssZ7rjoD+ALoQrBdZfX39gQMHIAQCAIArUVFR8csvv/D5/KioqJ7pue4I6A+gCyGTye677764uLjW1tZff/0VGnEBAHAZLBZLTU1NYWGhp6dnampqz/RcdwT0B9BFQyBNTU3Hjh2DEAgAAK6BVqvNy8srLy+HylMM6A+gi4ZAdDrdmTNnoBEXAADXoKys7Oeff4bKUxbQH0CXQy6Xjxs3TiwWV1VVQSMuAAAugMViKSsru3jxIlSesoD+ALocHh4eycnJYWFh0IgLAIBroNVqy8rKtFotVJ6ygP4AuhxCoVCpVD744INCoRAacQEAcJnkC1SeOgL6A+iKeHt7P/jgg2FhYdCICwCAyyRfoPLUEdAfQJcOgTAMA424AAC4RvIFKk8dAf0BdPUQCEzEBQCg+2KxWIqKis6cOePt7R0REQGVpyygP4AuilAoVCgUycnJWq32p59+ghAIAADd13P99OnTcXFxY8aM6ezL6UKA/gC6Ll5eXqNGjQoJCQEvMgAAunvl6YABAxITEzv7croQoD+ArotYLI6Pj3/ggQfAiwwAgG5deRoeHg5ttx0A/QF0gxBIUFBQRUXF8ePHIQQCAEC3qzzV6/WJiYnQdtsB0B9Al0YsFickJEyaNKm9vf348eMQAgEAoNtVnsbExEDlhzOgP4Du0QgTHBwMIRAAALpj5Sm03RIB/QF0Gy8QCIEAANCNKCkpOXPmDAx8oQH6A+gGeHt7jx07tl+/fjCRDgCAboHRaLx8+fLp06dh4AsN0B9AN0AoFIaEhIwbN85kMmVkZJSXl3f2FQEAAHCRl5d34sQJGPjCAegPoHvg4eGRmpoaGRmZlZX19ddfQxUIAABdFqPRmJ+fD2233ID+ALoHQqEwPDwcN8IcO3YM7FABAOiy5OXl/fOf/4S2W25AfwDdBplMdt999/Xr16+0tBQmwgAA0MWDH9B2yw3oD6A74efnN2nSJLPZDBNhAADomuTk5Bw6dAim3d4S0B9Ad0Imk40ePXrEiBEwFBcAgC7b9nLy5EmYdntLQH8A3Qx/f/8ZM2bI5fITJ06cPHmysy8HAADAjsViycrKOnbsGJ/Ph2m3twT0B9BdHdlbW1v/8Y9/QC8uAABdyvD05MmTPj4+ycnJMO2WG9AfQHe1I4NeXAAAuuC0F6FQOHjw4Mcee6yzr6irA/oD6MZ2ZNCLCwBAF6GpqenHH388efJkYGDgiBEjQkJCOvuKujqgP4BubEcGvbgAAHQFTCbT+fPnDx48KBQKBw4cOHHixM6+om4A6A+ge9uRmc3mH3744ciRIyBBAADoLKqrq3/66afy8vLAwMB7770X2l5uB9AfQPe2I4uLi1Or1bt374YsDAAAnYLRaDxz5szhw4fd3NxSUlIg+HGbgP4Aur0dmVgshiwMAACd2HN76NAhjUYTGxs7adIkCH7cJqA/gG6MTCZ78MEHJ0yYAFkYAAA6t+zUzc0Npr38JkB/AN0bf3//J598ErIwAADcfdrb28+dO3fw4EE+n5+QkPDQQw919hV1J0B/AC5SiApZGAAA7iYWi6WgoODw4cPl5eWenp6pqakQ/PhNgP4Auj2QhQEA4O7T1NT0/fffHzlyhM/nR0VFpaamdvYVdTNAfwCuAGRhAAC4mxiNxszMzIMHDzIM06tXr9GjR0Pw47cC+gNwwSzMV199VV9f39kXBQCAK/e87N27t7y83M3NbdSoUbNnz+7si+p+gP4AXASZTDZ69OiRI0eazeZjx44dPnwYsjAAAPyuPS+47BR6bv87QH8AroO/v//s2bPj4uKampo+++wzKAQBAOCOA5mXOwXoD8B1EIvF99xzD87ClJSUQCEIAAB3FpPJdOnSJci83BFAfwCu2QuDC0H27duXl5fX2RcFdCH0ev358+f1en1nXwjQ/bBYLOXl5V999RVkXu4IglWrVt2ZMwFA18Dd3V2hUGRnZ5eWlpaXl7e3t6ekpIhEos6+LuBu09TU9MMPP2RkZFy6dEkkEvn7+/N4vPLy8sWLFysUisjIyM6+QKA7YbFYGhoavvzyy+3btzMMI5fLJ02aNH369M6+rm6MsLMvAAB+l16YtLS0lpaWvLy8H3744Z577pkwYYJUKu3sSwO4sFgsOp3Ow8ODz78DcdmzZ88uW7asuLgY/9XDw2P16tXsYLCysrL//SWAHkVTU9M///lPXPbh5uY2dOjQxx57rLMvqnsD+RfABZHJZOPHj581a5ZUKlWr1Vu2bPn++++tVmtnXxdAxWw2r1+/Pjk5+aWXXtq3b19hYeH/kiJpaGjYtm2bl5fX1q1bT5069Z///CctLa2uro494A4WJldVVf373/82mUx36oRAF0Sv1586dWrnzp3l5eUikWjgwIFPPPFESEhIZ19X9wbiH4ArF4JcunTpyJEjJSUl+/bt+8Mf/iAWizv7ugAyJpOpqalJp9N9YwNHLIYPHz5jxoyUlBSJRPKbzpaTk/PDDz+8++6748aNw//y6quv4j8YDAa9Xu/r63unrvzcuXPbt28PDQ0NCwu7U+cEuhRGo/H06dPbtm0rLy8XCoUxMTGzZ8+Gnpf/HdAfgMvi7+8/Z84cooi5XQAAIABJREFUnU73448/ajQavV6P9YfJZPrxxx/d3d2HDRvW2dcI2Glra2MYZtWqVQMHDvTz8ystLc3MzPzqq6+efPJJhULx3HPPpaWl3aZ8tFqt58+fj42Nvffee52/qtPpSkpKPDw87uDFt7S04OsHXLXhZdeuXVeuXOHz+cHBwTNmzJgwYUJnX5crAPkXwGURCoURERHYEcRqtRqNRvxwOnLkyJtvvikQCDr7AoEbfPbZZ1999VVoaGj//v0VCsWwYcOWLFmSkZGxe/fuqKioV1555fXXX7927drtnMpgMKjV6tjY2ICAANoxd/a3X1JSotPp7uAJgS6CyWTCfsonT55kGMbHx+exxx6bMWNGZ1+XiwDxD8D1HUHS0tJOnTqF/6WoqGjnzp3z589PTk7u7KsDbuDm5qbT6SoqKhz/USKRjBw5cujQoZs3b163bl1iYmJaWtptnjAwMNDd3Z3jq3ekJqCtra2pqYlhmJUrV4rF4osXL+Kn1O7du5OSkv73lwB+V/R6/TfffHP8+PG2tjYfH59BgwaNGTNGoVA4io8dO3Z8/vnnDMNIpdKRI0dCzekdBOIfQI+oRZ05c6ZAIKivr3/nnXcSExMfffRRHo9XUlKSlpYGHmVdAT8/P4ZhvL29GxoaDhw40NDQ4HyMVqt1/KvVatVoNPX19Y6VqiaTqb29nWEYkUj0m/po9Hp9bW2tVqsl1ilbLBaNDbbO9MqVKw8//HBSUhK2MMjOzi4pKZkwYcJrr722ffv2mJiY3/Lugc7h+++//+STT7y8vEJDQ9Vq9fr168ePH3/8+HFn8eHm5jZ69OhFixZBzekdBOIfgOsjk8nuvfdevV6/a9cuhmEWLlyIe3FVKlV9fb1QCHdBF2Lv3r3vvvuuQqGYMGECj8fLzc1VqVTFxcWTJ0923Hqq1ep33333yy+/ZBhGoVCsXLly3LhxPB5vy5Yt7777LsMw48aNKykpCQkJ6fD7ValUMTExcrmc/Rej0bh3795169bh/M4LL7zw/PPPO3Zr5+TkrF279sSJEwzDDB48+O23346Ojlar1bW1tQqFwtPTMy8vb9euXaNGjeLxeHfr5wTcASZOnIi3IvivV65c+dOf/lRaWmq1WlUqFSs+oOHldwJWXqBHwOfzVSrVN99887e//Q1vtRmGyc/PHzx4cHBwcGdfHXCD5ORkhUJRWVm5detW/C8REREffPDBww8/zNaf1tfXL1++vLCwcM2aNcHBwZ9++unWrVsTExMVCkVYWJiPj8+1a9eO2mAYZsCAAQkJCePGjUtOTsZn4NnApzKZTDt27Ni4cePMmTMnTJhw4sSJHTt2JCUljRkzBh9w4cKF5cuXV1dX41aas2fPvvnmmxs2bBg1atTJkye9vLzOnDkza9YsLy8vEB/dDjZCZrFYCgoKtm7dGhMTM2nSJKPR+NNPP7HiIz4+Hhpefg9AfwA9hfz8/MbGRoPBYLFYeDxeXV3dpUuXEhMTOaoEgLvPoEGDPvjgg1deeSU3N/fxxx//y1/+0qFX1mg0bt68OTs7+7333ktJScEOHNu2bTMYDAzDTJgwYejQoatXrz58+PAjjzzi7e198eLFr7766tNPP507d+5f/vKXDi+XkZGxcePGF198ce7cuUKh0NPT89ixY2wxaUlJyWuvvcYwzK5duwYOHGi1Wrdv3/7jjz+aTCYej4cvDH9+qqur7+IPCbhjmM3mPXv2bNu2TaFQzJo1a8yYMVKptNkGTrvEx8fPmTMHGl5+D0B/AD2FmJgYX1/fOXPmOP5jY2PjpEmTOBolgLsMj8cbPHjwzp0733777b1794pEoiVLlvj4+LAH5OTkHDp0SCaTZWVlWa3W4uLijz766MEHHwwKCsIHyOVyhUIREhIyf/78iIgI3HNrNBrd3d3FYnFlZSV7Ko1Gs3//fqweMjMz9Xr9nj17JBJJ//798QEnTpwoKChYvXr1wIED8bXNteF82Waz+ff/2QB3HovFolKpKm2IRCJfX9+hQ4fiL0kkkiFDhsyfPx8iH78ToD+AnkLfvn2/+OKLkydP4idQfn7+wYMHAwMD+Xx+bW2tp6cnGLR3OuxTPCgoaM2aNdHR0Zs2bWpsbFy5cmWfPn1wzenJkyfDwsLGjh2bnp7+xhtvMAwzffr0l156ydGjjG1hwHjY6PASDMMUFBScP39+wYIFFy5cmDVrFsMw/fv3f+2118LDw/EBra2tISEhCQkJt/8WWlpaNm3aNG3aNLAj6xaIRKJly5Y99dRTWNfOmzdv6dKljzzyiFQqHTVq1PPPP5+YmNjZ1+iygP4AehByuZydAPLBBx/MnDlz5cqVbW1tP/74o5+f35AhQ0CCdBbYkMMxOCGRSJ5//vmIiIi///3vzz///Jo1ayIiIgwGQ3V1tVwunz59+jPPPKPVat3c3JzdUcVicXl5uUajIb6W1QauRRUIBCkpKc8++6xOp7NYLDKZzLGMQyqV5ubmHjp0aO7cuTKZjHg2uVweExPDypqCgoJdu3YNHToU9Ed3QSQSBf9/e/cC1PSV7wH8D4TwDE8BMUEEFSQir4tACAVStKIt7dYStb3L7Nad7o7uo7iys9PZ2e129s50745X2Xtbx7bu6mhblcDMtpX1tYpF0xCbIiAECA8NBBCCPAQij0DuwKm5XN5Ckn8e38849M+fP3DUsXxzzu/8TtCkjIyMTz755KOPPuJyucnJydu2bUPBqVFh/y3YLhaLxWAwRkZGKisrT58+ffPmTQMeCwLPZM6GHPb29i+++OLRo0c7OjqOHj06ODjo7OwcHh5++/btGzdukP26c7ZmX7dunZubm/7wuenYbHZdXR1p2hEWFubo6FhYWDg4OOjm5sZisWbUkG7bti0+Pj4/P5/P5+/bty/nqQMHDjx48IA8Q6pZFQqFVqvt7+8vKiqKiIgIDg423J8NGEtvb+/0kMpgMLZu3drW1tbe3h4aGorwYWwOZPM6gK2RSqVNTU0CgWBsbKy0tPTatWsqlcrJySkgIACzIKY3PDxcXl6ekZERHh4+40NsNjsoKEihUAgEAmdnZw6Ho1AoTp8+3d/fz2KxJiYmysvLT5069bvf/e7+/ft8Pp/BYDg7O9fW1vr7+89uAqbVaktLSwMDA+Pi4ry9vbVa7fHjx+vr61ksFpPJbGpq+uKLL/70pz999tlnZA5j27Ztfn5+XV1dMplMOUWr1aalpaWmpjo6OpISxZqamjNnzpw/f/7IkSNNTU2HDx/eunUrtsOYOZ1Od+LEiYMHD9bV1Y2NjfX29jY1NZ0+fdrb23v//v3Td2iDkdjhUFCwTS0tLa2trcnJyT09PSdPnjx+/DiDweBwOK+++uru3bvx0sec9fX1nThx4syZM/qNKmw2OyUlZf/+/frGXyMjIw4ODrObu+h0OoVC4eLiQv6KtVptcXFxfn6+frLEzc0tPj7+jTfe2LZt2xJ7w8hkst/85jcjIyM7d+58/fXX169fj/Bh5kZHR4eHhx8+fHj58mWZTFZZWdnX1+fm5paenv6LX/yCy+XSPUCbgPwBtm5kZEQqlb7//vsPHjzQaDReXl67d+/es2dPcHAwJkLM2cDAQHNz88jISFBQkJ+f30r6yI2NjSmVSrVa7efnx+FwnvW4XfIVSCXBsscApqHVaoeGhu7evdve3p6VlcVisegeke3C+gvYOgaD4evru2rVKq1W29bWNjAw0NjY2N3d7ejoyGaz8RPFbDk5Oa1evZp0IH2mVuuzOTg4+Pj4BAUF+fj4LC/HOExZyRjABIaHhxUKxfnz50+cODEyMrJ9+3YnJye6B2W7sP8FYLJBe2ZmJpvNdnNzKy4uHhgYuHz5slKp7Ojo2L59O9ZiACzd2NhYX1+fRCL5+OOP7927R1EUNtbSDvkDYBKTyYyOjvby8vLw8Lh27VpLS0tlZaVSqWxpacnKyuJyuViLAbDcBZfa2tozZ84UFxeTmwwGg8lkrnDaDFYI6y8A37O3t/fx8YmOjmaxWFqtVq1WDwwMKBQKlUplZ2cXEhKCtRgACzIxMTE0NFRfX3/hwoUPPvhAJpORf+Zubm5hYWE7duyIjY1FpTCNUH8KMNPo6Oi9e/fOnTtXXFys0WgYDEZwcPDrr7+ekpKColTrplKpZt/kcDh0jAVWZHh4uK2t7fr162fPnm1paSE3nZyc1qxZs3379pycHKyr0g75A2AOWq1WqVSeO3dOLBaTfTEsFksgEOzcuTM9PR0RxLBEIlFbW5v+Z39ra6tRI8WcIeNZTQ8l5JrH4yUmJgYFBSGv0Gt0dLSnp+fOnTv6Ug+yNcnDwyMmJmb//v04z8VMIH8AzGtwcPDGjRuXLl0irVGZTGZERMQrr7ySkZHh7++PFLISIpFIKpVKJBKDpAFzkxQdzYuPz96zh7NmDeXkNPkLjG9sbOzx48cVFRWnTp26desWuclgMNzc3CIiIoRC4fbt2z09PekeJnwP+QNgIaOjo3K5/MsvvyRFqRRFeXl57dq167nnnsNEyPLk5eWJRKLZ94UCweRcgp8fe9UqztMTiVVdXfoH2rq75/yC7FWrZtzRf7opSeVySXW1Sq1WqdX6m0lcLi8yMvullzibN1MsFoKIUZNHfX19UVHRtWvXSFd1kjyCg4N37Njx8ssvY8HF3CB/ACyur6/vq6++unr1qkwmw0TIsuXn5x87dmz6HaFAkBgRwYuM5Pj5UdZCUlNT9PXXJIvobyZxubl79vDS0ig2GynE2MnD3t7e1dU1NDQUycOcIX8APENRqkgkEovFmAh5ViqV6vDhw2VlZeRdoUDwWloab/NmyqrNDiJJXO5//frXnNRURJCVGx0d7evra2xsnJE8nJ2dAwMDMzIyUGRq5pA/AJZKq9U+fPiwpKRkxkRIVlYWtsYsQCKR7Nu3j1wf2rMnOz3dmmY7FiWpqckvKCiTy/V3jhw8KMzNRQRZtuHh4Z6enurq6oKCgjt37sxIHsnJyXv37kV7MfOH/AGw0ooQsjXmhRde4PF4q2bVItg4ffjgrFlz5Kc/tfo5j/lIamryPvxQPxFyKCcn9/e/RwR5JhMTE0+ePOnv75fJZNP3tpA6j9WrVyckJCB5WBDkDwDDVISEhYWlp6cLBAI0S50zfIj/+le6h0O/ve++q58IOfSTn+T+4Q90j8gykB6mnZ2dUqn0woULM3bVstls1HlYIuQPgBVNhFy8eFHfI8TV1TUuLu7555/HqTGk5oPP50+GDzb7wnvvcbDvcUre8eOikhJyff7sWV5qKt0jsoDyUpVKdeXKla+++krfSYwkj40bN7700ktpaWn452aJkD8ADNAj5MqVK2VlZd1TG0S9vLyysrJeeOGF+Ph4W54I2bt3Lyk4Pf+Xv/BCQugejpnOgojFYvQrW7i8tLi4uLS0dEbyCA8P37VrF5KHRUP+AFip0dFRhUJRUlJy8+ZNuVyur0vdtWtXfHy8bS7H6FdeDh08mDvV2AOm4x88SGpBDh06lJubS/dwzIhWq9VoNIODg3OWl3p7e4eGhv7gBz9AJzErgPwBYBgajaa8vPzGlM7OTrIcs3Xr1p07d/L5fFt7lcbn80ljU/HJk1h5mU1SU7Pv6dmfmAKZsdRSWlp65cqVGUUeq1atQnmplWHQPQAAK+Hq6pqSkhIZGblhwwaxWEyWY8RicVNTU01NjU0tx6imkLJThI858TZvFgoEpBCksLDQxqdAyH7aBw8eYKnFpmD+A8DAsByj73N65O23hTjrawlTIEqlkrLVCY+hoaGKioqzZ8/W19fr+6a7urqyWCwstVg35A8A0y3HkN0xVt+1XV95qpzrnBeYvRfG1pZgFq4tDQ4OTk5OzszMxFKLdcP6C4Bxl2PCw8NlMtmNGze6u7tv375dXV3d2NiYnJxsxc3KSPjgBAbSPRBzlxgRQfKHRCIRCoWUzUx41NXVTa8txYSHbUL+ADAiLy+v1157LTExMSQkRCKRyGSyvr6+wsLCqqoquVzO4/GsryiEVH5MHvKSnk73WMydUCDIF4lUarVUKrXi/KHvWzpfhQcmPGwT1l8ATNes7NKlSzKZzLqLQkQiUV5e3mTbjz/+0Wa7rS+jF4hVloCQCY9Hjx5JpdIvv/xSX+Hh6Ojo7u5OjqjFhIfNwvwHgCkwmcyYmJiwsLDy8vKbN2+SlqmVlZUNDQ3WWhQS5O9P9xAsQHZ6OskfKpXKakpAxsbGBgcHnzx50tTUdPnyZf2EB4PB8PDwcHd3X7du3fPPP5+UlIQJD1uG/AFg6qKQmJiY2NjYW7dulZWVdXZ2kqKQ+vr62NhYHo9n6SlE/0PUpg65XTaOdaU0/U7aGzdulJWVzejhQdZZ0tLSwsPDMeEByB8Apubu7r5jx47o6OioqCh9p5CioiKxWFxVVWXdpakwg3UsUc23k5bEDjc3t+DgYKyzwAzIHwA0YDAYHA4nOzs7Kipq8+bNUqm0urpapVJZTWkqJj+WjuPnp1KrW1tbLW79Zb51FkdHR29vb1LesWPHDrQOgzkhfwDQhslkRkZGhoWFpaamlpaWkg0y1dXVCoVCLBZnZmZGRkZadAqBpeBFRopKSvT7hizoiJYZ6ywkdri4uKC8A5YC+QPAXFJIcnKyfoNMZWVlbW2tVW6QAUvvG6ZSqcRicWlpKVlnmVFVGh0djfIOWArkDwCz2yBz69YtfQohG2See+45S0khQUFBk/+xs6N7IGD0vmGOjo6+vr6oKoXlQf4AMLsNMnFxcdO36d6+fbu8vNyytumqurroHgIYLHYolcoZ5R2+vr4eHh4cDgdVpbBsyB8A5rtNNz4+/s6dO+QEGUvZpmtxRZSw9KpSX19fbGYBQ0H+ADBT7u7umZmZSUlJmzZtqqurIymEbNO9e/eumaeQySkQtRq7YIxNq9UODQ2Nj497eno6ODgYJHbMrirVxw5sZgEDQv4AMGteXl579uzp6+sLDw+/e/cuaVmmbxaSmJgYExNjzikElqitre1ZP2VsbKy5ufmLL74YGxs7cOCAj4/PyjezVFZWkqpSxA4wNuQPAIs5x47P58fGxupTSGFhIZkIQcsyGzQ8PHzv3r1Tp05dv379lVdeedbJD33sePjw4fTNLKRj2Nq1axE7wNiQPwAsqWXZjBSiVCqbmppIy7KEhIQtW7aYTwpp7erC+stStHZ2PuunaDSar7/++sMPP2xoaEhNTc3JyVl6KQapKlUqlYgdQC/kDwCLTyHNzc0KhaK0tDQ1NdUcUgiHw7GgbloWR6PRXL58+dixY93d3QKB4Oc///lS2nxN38zyj3/849q1a4gdQC/kDwDLYxEpRNXbS+N3t0oTExMajebq1av5+fk9PT2ZmZmHDh1aODHMuYeWxI6QkBAOh4PYAXRB/gCwVBaRQmCJFp0x0mq1nZ2dxcXFn376qUajEQqF+/fvny83zI4d7e3trq6u7u7uJHZgAy3QDvkDwLIhhdiC0dHRxsbGs2fPnj9/PiAg4NVXX83JyZkdPmbHjo6ODnd3dxcXl6ioKHQpBbOC/AFgEynE9AfqtqEFqoFoNJo7d+6cPHlSIpEEBgbm5OQcOHBgibFj69atOJMFzBPyB4BNpBBrPVBXp9MNj446M5l285w4s+gDFlHwcezYsY6OjvXr1//4xz9+4403yEcRO8CiIX8A2EQKaWhoIAfqWlMK0el0py5dKpZI/uftt9fMtcC06AOTSxtjY59cvBgRHCyIjSUZZXh0VNHauoHNdnV2puijL/g4e/ZsV1dXTEzMm2+++eKLLyJ2gHVA/gCw/hQSFxdHOrhbWQoZn5jo7OlZ6+/v4ea2vAcoilL391//7rvPrl49kZcXtX49RVGVjY173n03i8//889+5u7iQtFBq9U+ePDgb3/72+eff+7q6ioQCN56661169a1tLTMLilF7ABLhPwBYP0phHRw158jY5oUYoIjcIeGh+93dERv2DBfSlj0AYqiunp765TKoeHhy1Lp5pAQB3v7jkePKIpqVKm6entNkD9UavVkF7LWVv0djUbT0NBwfoqLi0tiYuIPf/hDjUZz9OjR6RtoUVIKFg35A8C2zpHZtGlTU1OTTCaTy+XGTSETE5SRVTc3y+rqfpSZuewHKIrq7u8fGh6efPj+/f7BQU93d8VUFHj0+DG5T1fBR2trq4uLy8aNG52cnN555x197CDtwrCBFiwd8geAzaUQjUZTXl5+69atGSkkIiLCgnbq6nS6O7W1EevWbeRwlvcAoXz4MCQw0NPNrVapbOvu1o6PVzY1kXmRkdFRiqaCj5aWFgaDMTExUVlZKZfL0aUUrA/yB4DNcXV1TUlJiYuLm5FCwsLCDNIvxDTN1x9rNLVKZVxYmO88cwCLPkBKTZvb29cGBGQmJr7z0UdVTU2+Hh63q6ook5uYmJDL5efOnfv888/JHTs7OxcXF19f39DQUMQOsD7IHwA2as4UYkFdy+63t1c3N/80K8vB3n55D1AU1d7dXa5QPB8Xl7Jly7+Fh9+uqhqfmEiIiBDExv7n0xxgAjqdrre39/DhwwqFgiQPe3v7wMDAtLS0pKQkcryLTqdTKpUURdlPWeCrMRgMd3d3t/lLbgHMAfIHgE2bnkLEYnF1dbVMJjP/FDI+MXG9vDwyNHRjUNDyHiA/0aVyea1SeXjfPrafH3/Llv8uLKQo6lfZ2QkREW7Oziq1On7TJsok7t+/r9VqSfhgMpkuLi7Dw8PXpsx40tnZeeGyDx8fn5dffnn37t1GHjLAiiB/AMD3KSQhIUEul1+5ckUul1dXV588eXIlKWQZx8ovXXt3d2lFRRaf7znPq/xFH5jcedvXd1EiSYmKil6/3sHefndqamlFRYNKlRYd7ePhsTYgoK27mzIJOzs7BwcHNptN3p2YmBgfHycJiVxMTCEXQ0NDj6Z26JCbZDrE3t7ewcGBfB21Wi2Xy5E/wMwhfwDA95hMZkxMDJfLJfMfUql05SnESEorKysaG3//ox8t+wGKor6prr5dVfWr7GxSIBISGPgfb73V2dMTs3Hjk5GRkMDANrWa9E6ljM/Hx6egoIBcP3nypL+/f8bFwMDA9Dv6axcXF09PT/LWycnJ09PTx8cnPDzcBGMGWAnkDwD4f5hMZmRkJKlFNdsU8mjqZ/BjjUan083ZWH3RB+pbWk7985/+3t4ZcXH6ApEtoaFbQkMpinJ3cQkLCrpVVfXo8WO2SX6zDg4Oq1evNsE3AjATyB8AsHgK+fbbb+/fv3/u3LlFU4h+80tQQIDxhhfg40NR1Jvvvx+7cSPradsSlVrd2dPzckrK4b17F33gX999V9HYKBQIwuYqELGzs4sMDc0XiZrb202TPwBsDfIHACyeQtLT0ysqKsrKyqqqqpaSQoxtR0KC/MEDUUnJ3YaGGR86969/Bfn7//v27Qs/sCMh4dva2je2bZvvkJdNa9fGbNhwu6qKt3kzw8HB2P1PAWyNnU6no3sMAGABRkdHGxsb9Smkr6+PzWbPTiEqlYrP51MUJRQIjhw8aNQhjWm1g0+ekGumoyOTwRh88qR3YMDPy4vMeSz6wAK04+PHCgoKSko+yM1N5HKN97sIFgopiuJwOGKx2HjfBcDcYP4DAJaEyWRyudwNGzbExMTcu3ePHKurnwvh8XimP83OkcHwZrGm3/FmsabfWfSBBTAcHN7Ozt6VlLTWmAtJk8nDzw9TIGCDkD8A4JlTSFhYGJ/Pj42N1acQsVhMzpEJDAykrAXT0XFzSAjdowCwTsgfALDMY3Vfe+216Snk448/Xrt2LVl8IS/r6R4mAJgv5A8AMGQK+fTTT8lHu5+2qYCl4Cx4SB6A9UH+AACDpZCoqKiLFy+SOsp7U6fIAgDMCfkDAAyWQrKzs+3t7b/55hudTsdg4H8vADCvhQ5RBAB4JkwmMzg4mOzqj9mwge7hWAYUyoBtQv4AAKPYtHYt3UMAAPOF/AEARsHx96d7CABgvpA/AADoFzTXMTQAVgz5AwCMIgjzHwAwP+QPADAKlFUuETkoGP0/wNYgfwAAAICpIX8AgOFh8gMAFob8AQAAAKaG/AEAhof5j6Vr7eykKIrNZtM9EACTQv4AAMNTqdV0D8Fi4M8KbBPyBwAYgZ0d3SOwsPzR1tZG90AATAr5AwCANpj8AJuF/AEAhqfq6qJ7CJZBUl1N9xAA6IH8AQBGgVf2S9HW3U0uUH8Ktgb5AwAMCeeYPBNRSQm5EAqFdI8FwKSQPwDAkDhTsLKwFCq1mswScQID6R4LgKkhfwCAUUjr6+kegrkrvHmTXHBWr6Z7LACmhvwBAAbG4/Em22o9rWyARUtkeCkpdI8FwNSQPwDAwBITEymKKqusRAnqAlRqNSn+4Pj75+bl0T0cAFND/gAAAxMKhaQEJL+oiO6xWMDiizA7m+6xANAA+QMADI/s5hBdv44pkDmp1OpjBQWTkx8BAbm//S3dwwGgAfIHABhednY2mQLRv8qH6Q5/8AFZeTly5AjdYwGgB/IHABgeh8MhUyDHCgryRSK6h2Ne8o4fL5PLKYo68uc/81JT6R4OAD3sdDodTd8aAKxcXl6eaCp8iI8f5/j50T0cs7D33XdJ+Dj/97/zMjLoHg4AbZA/AMCI+Hy+SqXi+PldeO89G48gkpqavA8/JAUxCB8AyB8AYEQqlWrv3r0qlWpyueHgQaFAQNkeUUlJ4c2bZNqDExh45Ngx0iIFwJYhfwCA6RZikrjc7PR0XmSkjcyFTE8eFEUd+uUv0eoDgED+AABTyM/PFxUUqNrayLtJXC4vMjKRyw3y97eyLCIqKZHW1kqqq6fvPT506FBubi6t4wIwL8gfAGAiEokkPz+/rKxsxv0kLjcoIGBybeJpEGGvWrXSb+bo+P0Fg/F/b///kfcz7s9Lq518Oz4++Wv6u9PGKa2tJUfuzeh3IhQKExMTcbYtwGzIHwBgUhKJpKgrV96sAAAAmklEQVSoSCKRkKIQ68PhcHg8HmIHwMKQPwCAHiSCtLW1kQvSrywoKEj/QGtrK7nQJxUziSxkqNMHzOFw2Gw2j8cjNwFgUcgfAGB5SBCZHVCma3taazL7c+dMCWw2e/bNGakI8QLAUJA/AAAAwNTQfx0AAABMDfkDAAAATA35AwAAAEwN+QMAAABMDfkDAAAATA35AwAAACgT+1/GOjDnGoMowgAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "1",
   "metadata": {},
   "source": [
    "![1_3ic-K5U5ZWiQ8NeXj4bX8g.png](attachment:2282b751-b576-4770-b12e-00d8fbc4cc89.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure the Experiment Environment\n",
    "!pip install -e .[all]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3",
   "metadata": {},
   "source": [
    "## Experimental Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4",
   "metadata": {},
   "source": [
    "### Load Experiment Configuration\n",
    "\n",
    "The following code loads a pre-defined YAML experiment configuration template for GSM8K GRPO through `load_expr_config`.\n",
    "\n",
    "This template sets up hyper-parameters including optimizer, model, learning rate, and so on. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dataclasses import asdict, dataclass\n",
    "\n",
    "from areal.api.cli_args import GRPOConfig, load_expr_config\n",
    "\n",
    "args = [\"--config\", \"examples/math/gsm8k_grpo.yaml\"]\n",
    "config, _ = load_expr_config(args, GRPOConfig)\n",
    "config: GRPOConfig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6",
   "metadata": {},
   "source": [
    "### Environment Variable\n",
    "\n",
    "We specify the IP address and ports for SGLang servers and PyTorch distributed training through corresponding environment variables.\n",
    "\n",
    "These environment variables will be loaded when the AReaL engines (rollout/training) are initialized.\n",
    "\n",
    "\n",
    "***When launching experiments through AReaL launchers instead of jupyter notebook, these environment variables will be set by the launcher by default and are unnecessary to be set by the users.***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "from areal.utils.network import find_free_ports\n",
    "\n",
    "SGLANG_PORT, MASTER_PORT = 11451, 14514\n",
    "\n",
    "SGLANG_HOST = \"127.0.0.1\"\n",
    "\n",
    "# Environment variables used by inference/train engines\n",
    "import os\n",
    "\n",
    "os.environ[\"AREAL_LLM_SERVER_ADDRS\"] = f\"{SGLANG_HOST}:{SGLANG_PORT}\"\n",
    "os.environ[\"MASTER_ADDR\"] = \"127.0.0.1\"\n",
    "os.environ[\"MASTER_PORT\"] = str(MASTER_PORT)\n",
    "os.environ[\"RANK\"] = str(0)\n",
    "os.environ[\"WORLD_SIZE\"] = str(1)\n",
    "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"true\"\n",
    "os.environ[\"LOCAL_RANK\"] = str(0)\n",
    "os.environ[\"NCCL_CUMEM_ENABLE\"] = \"0\"\n",
    "os.environ[\"NCCL_NVLS_ENABLE\"] = \"0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8",
   "metadata": {},
   "source": [
    "### Launch SGLang Server\n",
    "\n",
    "AReaL seperates trajectory rollouts from training, where rollouts and training are executed asynchronously, allowing for full GPU utilizing and fast end-to-end training.\n",
    "\n",
    "In this example, the reinforcement learning algorithm (GRPO) runs on GPU 0.\n",
    "\n",
    "In GPU 1, an inference service is launched for LLM generation. The RL algorithm can send generation request to the inference service.\n",
    "\n",
    "The following code launches a SGLang server on GPU 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import subprocess\n",
    "import sys\n",
    "\n",
    "# launch sglang server\n",
    "from areal.api.cli_args import SGLangConfig\n",
    "from areal.utils.network import find_free_ports\n",
    "\n",
    "config.sglang.log_level = \"info\"\n",
    "config.sglang.decode_log_interval = 10\n",
    "sglang_cmd = SGLangConfig.build_cmd(\n",
    "    config.sglang,\n",
    "    tp_size=1,\n",
    "    base_gpu_id=1,\n",
    "    host=SGLANG_HOST,\n",
    "    port=SGLANG_PORT,\n",
    ")\n",
    "sglang_process = subprocess.Popen(\n",
    "    sglang_cmd,\n",
    "    stdout=sys.stdout,\n",
    "    stderr=sys.stderr,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10",
   "metadata": {},
   "source": [
    "### Load GSM8k Dataset\n",
    "\n",
    "Load GSM8k dataset using Huggingface `datasets` package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load gsm8k dataset\n",
    "from datasets import load_dataset\n",
    "\n",
    "dataset = load_dataset(path=\"openai/gsm8k\", name=\"main\", split=\"train\")\n",
    "print(f\">>> dataset column names: {dataset.column_names}\")\n",
    "print(f\">>> example data: {dataset[0]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12",
   "metadata": {},
   "source": [
    "### Load Necessary Python Packages and Modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13",
   "metadata": {},
   "outputs": [],
   "source": [
    "import asyncio\n",
    "import functools\n",
    "import os\n",
    "import time\n",
    "import uuid\n",
    "\n",
    "import colorama\n",
    "import torch\n",
    "from transformers import AutoTokenizer, PreTrainedTokenizerFast\n",
    "\n",
    "from areal.api.cli_args import GenerationHyperparameters\n",
    "from areal.api.engine_api import InferenceEngine\n",
    "from areal.api.io_struct import (\n",
    "    AllocationMode,\n",
    "    FinetuneSpec,\n",
    "    ModelRequest,\n",
    "    WeightUpdateMeta,\n",
    ")\n",
    "from areal.api.workflow_api import RolloutWorkflow\n",
    "from areal.engine.ppo.actor import FSDPPPOActor\n",
    "from areal.engine.sglang_remote import RemoteSGLangEngine\n",
    "from areal.utils.data import concat_padded_tensors, tensor_container_to\n",
    "from areal.utils.device import log_gpu_stats\n",
    "\n",
    "tokenizer = AutoTokenizer.from_pretrained(config.tokenizer_path)\n",
    "if tokenizer.pad_token_id is None:\n",
    "    tokenizer.pad_token_id = tokenizer.eos_token_id"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14",
   "metadata": {},
   "source": [
    "Process the data format into a compatible chat format for OpenAI client."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15",
   "metadata": {},
   "outputs": [],
   "source": [
    "def process(sample):\n",
    "    messages = [{\"role\": \"user\", \"content\": sample[\"question\"]}]\n",
    "    return {\"messages\": messages}\n",
    "\n",
    "\n",
    "dataset = dataset.map(process).remove_columns([\"question\"])\n",
    "print(f\">>> example data: {dataset[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16",
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchdata.stateful_dataloader import StatefulDataLoader\n",
    "\n",
    "dataloader = StatefulDataLoader(\n",
    "    dataset,\n",
    "    batch_size=config.train_dataset.batch_size,\n",
    "    shuffle=True,\n",
    "    collate_fn=lambda x: x,\n",
    "    drop_last=True,\n",
    ")\n",
    "from itertools import cycle\n",
    "\n",
    "data_generator = cycle(dataloader)\n",
    "\n",
    "ft_spec = FinetuneSpec(\n",
    "    total_train_epochs=config.total_train_epochs,\n",
    "    dataset_size=len(dataloader) * config.train_dataset.batch_size,\n",
    "    train_batch_size=config.train_dataset.batch_size,\n",
    ")\n",
    "\n",
    "x = next(data_generator)\n",
    "print(f\">>> The type of a batch is: {type(x)}\\n\")\n",
    "print(f\">>> Each piece of data has keys: {x[0].keys()}\\n\")\n",
    "print(f\">>> Example rollout input: {x[0]['messages']}\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17",
   "metadata": {},
   "source": [
    "## A Simple Single-Turn Workflow\n",
    "\n",
    "A single-turn workflow utilizes the inference engine to generate a response for a answer, and uses a reward function to compute the reward."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18",
   "metadata": {},
   "source": [
    "### Reward Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19",
   "metadata": {},
   "outputs": [],
   "source": [
    "from concurrent.futures import ProcessPoolExecutor\n",
    "\n",
    "rw_executor = ProcessPoolExecutor(max_workers=4)\n",
    "\n",
    "from areal.reward.math_parser import extract_answer, math_equal\n",
    "\n",
    "REWARD_TIMEOUT_SECONDS = 15\n",
    "\n",
    "\n",
    "def reward_fn(generated, answer):\n",
    "    try:\n",
    "        x = extract_answer(generated, \"math\", use_last_number=True)\n",
    "        y = extract_answer(answer, \"math\", use_last_number=True)\n",
    "\n",
    "        if x is None or x.strip() in [\"None\", \"none\", \"\"]:\n",
    "            return 0.0\n",
    "        elif y is None or y.strip() in [\"None\", \"none\", \"\"]:\n",
    "            return 0.0\n",
    "        return float(math_equal(x, y, timeout=False))\n",
    "    except:\n",
    "        return 0.0\n",
    "\n",
    "\n",
    "# TODO: examine reward function\n",
    "reward_fn(\n",
    "    \"\\boxed{72}\",\n",
    "    \"Natalia sold 48/2 = <<48/2=24>>24 clips in May.\\nNatalia sold 48+24 = <<48+24=72>>72 clips altogether in April and May.\\n#### 72\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20",
   "metadata": {},
   "source": [
    "### Single-Turn Workflow\n",
    "\n",
    "The single-turn workflow is also called *Reinforcement Learning from Verifiable Rewards, RLVR*.\n",
    "\n",
    "A RLVR workflow is extremely clean:\n",
    "\n",
    "1. Load a datapoint from the dataset;\n",
    "2. Call the inference engine to generate a response;\n",
    "3. Compute reward using the reward function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: implement\n",
    "\n",
    "\n",
    "class RLVRWorkflow:\n",
    "    def __init__(self, gconfig, verbose):\n",
    "        self.gconfig = gconfig\n",
    "        self.verbose = verbose\n",
    "\n",
    "    async def gen(self, engine, input_ids, rid, answer):\n",
    "        req = ModelRequest(rid=rid, input_ids=input_ids, gconfig=self.gconfig)\n",
    "        resp = await engine.agenerate(req)\n",
    "        loop = asyncio.get_event_loop()\n",
    "        completions_str = tokenizer.decode(resp.output_tokens)\n",
    "        reward = await loop.run_in_executor(\n",
    "            rw_executor, functools.partial(reward_fn, completions_str, answer)\n",
    "        )\n",
    "        if self.verbose:\n",
    "            print(f\">>> prompt str: {tokenizer.decode(resp.input_tokens)}\")\n",
    "            print(f\">>> generated: {tokenizer.decode(resp.output_tokens)}\")\n",
    "            print(f\">>> answer: {answer}\")\n",
    "            print(f\">>> reward: {reward}\")\n",
    "        return resp, reward\n",
    "\n",
    "    async def arun_episode(self, engine, data):\n",
    "        assert self.gconfig.n_samples == 1\n",
    "        prompt_ids = tokenizer.apply_chat_template(\n",
    "            data[\"messages\"],\n",
    "            apply_chat_template=True,\n",
    "            tokenize=True,\n",
    "        )\n",
    "        resp, reward = await self.gen(\n",
    "            engine, prompt_ids, uuid.uuid4().hex, data[\"answer\"]\n",
    "        )\n",
    "        input_ids = resp.input_tokens + resp.output_tokens\n",
    "        logprobs = [0.0] * resp.input_len + resp.output_logprobs\n",
    "        loss_mask = [0] * resp.input_len + [1] * resp.output_len\n",
    "\n",
    "        res = dict(\n",
    "            input_ids=torch.tensor(input_ids),\n",
    "            logprobs=torch.tensor(logprobs),\n",
    "            loss_mask=torch.tensor(loss_mask),\n",
    "            reward=torch.tensor(reward),\n",
    "            attention_mask=torch.ones(len(input_ids)),\n",
    "        )\n",
    "        # [bs, seqlen]\n",
    "        res = {k: v.unsqueeze(0) for k, v in res.items()}\n",
    "        return res"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22",
   "metadata": {},
   "source": [
    "### Test Single-Turn Workflow\n",
    "\n",
    "1. Create the inference engine;\n",
    "2. Create the workflow;\n",
    "3. Collect a batch of data using the inference engine and workflow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "23",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize inference engine\n",
    "rollout = RemoteSGLangEngine(config.rollout)\n",
    "rollout.initialize()\n",
    "try:\n",
    "    # TODO: create workflow\n",
    "    workflow = RLVRWorkflow(\n",
    "        gconfig=GenerationHyperparameters(max_new_tokens=512), verbose=True\n",
    "    )\n",
    "    sample_data = next(data_generator)[:2]\n",
    "    res = rollout.rollout_batch(sample_data, workflow=workflow)\n",
    "    print(res)\n",
    "finally:\n",
    "    rollout.destroy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24",
   "metadata": {},
   "source": [
    "## Extending Single-Turn Workflow into Multi-Turn Reflection Workflow\n",
    "\n",
    "The core logic: a while loop is executed that, when the LLM produces an incorrect answer, a prompt is injected to ask the LLM to reflect and generate the next answer.\n",
    "\n",
    "To avoid the LLM from endless reflection, a discount factor should be added to multi-turn reward."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25",
   "metadata": {},
   "source": [
    "### Reflection Prompt\n",
    "\n",
    "Since there may exist inconsistency of token ids when encoding and decoding a sequence, we need to tokenize the reflection prompt in advance and add the token ids of the reflection prompt into the trajectory during execution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26",
   "metadata": {},
   "outputs": [],
   "source": [
    "messages = [{\"role\": \"assistant\", \"content\": \"some random message.\"}]\n",
    "prefix = tokenizer.apply_chat_template(messages, tokenize=False)\n",
    "s1 = tokenizer.apply_chat_template(messages, tokenize=True)\n",
    "messages += [\n",
    "    {\n",
    "        \"role\": \"user\",\n",
    "        \"content\": \"\\nYour answer is either wrong or not parsable to the reward function. Please try to answer it again.\",\n",
    "    }\n",
    "]\n",
    "s2 = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True)\n",
    "s = tokenizer.apply_chat_template(messages, tokenize=False)\n",
    "reflection_tokens = s2[len(s1) :]\n",
    "print(f\">>> prefix string:\\n{prefix}\\n\")\n",
    "print(f\">>> prefix token id:\\n{s1}\\n\")\n",
    "print(f\">>> whole string:\\n{s}\\n\")\n",
    "print(f\">>> whole sentence token id:\\n{s2}\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27",
   "metadata": {},
   "outputs": [],
   "source": [
    "class ReflectionWorkflow:\n",
    "    def __init__(self, gconfig, max_turns, turn_discount, verbose=False):\n",
    "        self.gconfig = gconfig\n",
    "        self.max_turns = max_turns\n",
    "        self.turn_discount = turn_discount\n",
    "        self.verbose = verbose\n",
    "\n",
    "    async def arun_episode(self, engine: InferenceEngine, data):\n",
    "        messages = data[\"messages\"]\n",
    "        # Convert the prompt into input_ids\n",
    "        input_ids = tokenizer.apply_chat_template(\n",
    "            messages,\n",
    "            tokenize=True,\n",
    "            add_generation_prompt=True,\n",
    "        )\n",
    "        assert self.gconfig.n_samples == 1\n",
    "        t = reward = 0\n",
    "        discount = 1\n",
    "        rid = uuid.uuid4().hex\n",
    "        seq = []\n",
    "        logprobs = []\n",
    "        loss_mask = []\n",
    "        # TODO: implement reflection\n",
    "        while t < self.max_turns and reward == 0:\n",
    "            resp, reward = await RLVRWorkflow(self.gconfig, self.verbose).gen(\n",
    "                engine, input_ids, rid, data[\"answer\"]\n",
    "            )\n",
    "            input_len = resp.input_len - len(seq)\n",
    "            seq += resp.input_tokens[-input_len:] + resp.output_tokens\n",
    "            logprobs += [0.0] * input_len + resp.output_logprobs\n",
    "            loss_mask += [0] * input_len + [1] * resp.output_len\n",
    "            t += 1\n",
    "            if reward == 0:\n",
    "                input_ids += resp.output_tokens\n",
    "                if input_ids[-1] != tokenizer.eos_token_id:\n",
    "                    input_ids += [tokenizer.eos_token_id]\n",
    "                input_ids += reflection_tokens\n",
    "                discount *= self.turn_discount\n",
    "\n",
    "        res = dict(\n",
    "            input_ids=torch.tensor(seq),\n",
    "            logprobs=torch.tensor(logprobs),\n",
    "            loss_mask=torch.tensor(loss_mask),\n",
    "            rewards=torch.tensor(float(reward * discount)),\n",
    "            attention_mask=torch.ones(len(seq), dtype=torch.bool),\n",
    "        )\n",
    "        res = {k: v.unsqueeze(0) for k, v in res.items()}\n",
    "        return res"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28",
   "metadata": {},
   "source": [
    "### Test Multi-Turn Reflection Workflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize inference engine\n",
    "rollout = RemoteSGLangEngine(config.rollout)\n",
    "rollout.initialize()\n",
    "try:\n",
    "    # create workflow\n",
    "    workflow = ReflectionWorkflow(\n",
    "        gconfig=GenerationHyperparameters(n_samples=1, max_new_tokens=512),\n",
    "        max_turns=5,\n",
    "        turn_discount=0.9,\n",
    "        verbose=True,\n",
    "    )\n",
    "    sample_data = next(data_generator)[:2]\n",
    "    res = rollout.rollout_batch(sample_data, workflow=workflow)\n",
    "    print(res)\n",
    "finally:\n",
    "    rollout.destroy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30",
   "metadata": {},
   "source": [
    "## Generate Multiple Trajectories for A Single Question\n",
    "\n",
    "RL algorithms such as GRPO generate a group of multiple trajectories for each single question.\n",
    "\n",
    "In the workflow, we can efficiently generate multiple trajectories by using `asyncio` to pose multiple generation request to the inference engine concurrently."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31",
   "metadata": {},
   "outputs": [],
   "source": [
    "class GroupedReflectionWorkflow:\n",
    "    def __init__(self, gconfig, max_turns, turn_discount, verbose=False):\n",
    "        self.gconfig = gconfig\n",
    "        self.max_turns = max_turns\n",
    "        self.turn_discount = turn_discount\n",
    "        self.verbose = verbose\n",
    "\n",
    "    async def arun_episode(self, engine, data):\n",
    "        workflows = [\n",
    "            ReflectionWorkflow(\n",
    "                self.gconfig.new(n_samples=1),\n",
    "                self.max_turns,\n",
    "                self.turn_discount,\n",
    "                self.verbose,\n",
    "            )\n",
    "            for _ in range(self.gconfig.n_samples)\n",
    "        ]\n",
    "        tasks = [workflow.arun_episode(engine, data) for workflow in workflows]\n",
    "        results = await asyncio.gather(*tasks)\n",
    "        return concat_padded_tensors(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize inference engine\n",
    "rollout = RemoteSGLangEngine(config.rollout)\n",
    "rollout.initialize()\n",
    "try:\n",
    "    # create workflow\n",
    "    workflow = GroupedReflectionWorkflow(\n",
    "        gconfig=GenerationHyperparameters(n_samples=3, max_new_tokens=512),\n",
    "        max_turns=5,\n",
    "        turn_discount=0.9,\n",
    "        verbose=False,\n",
    "    )\n",
    "    sample_data = next(data_generator)[:2]\n",
    "    res = rollout.rollout_batch(sample_data, workflow=workflow)\n",
    "    print(res)\n",
    "finally:\n",
    "    rollout.destroy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33",
   "metadata": {},
   "source": [
    "## Integrating the Workflow into RL Training \n",
    "\n",
    "\n",
    "We've already tested the inference workflow. Next, we need to integrate this workflow into the training process.\n",
    "\n",
    "This requires creating a separate training engine specifically for PPO. Within the training loop, inference and training are called."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34",
   "metadata": {},
   "source": [
    "### Synchronous Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35",
   "metadata": {},
   "outputs": [],
   "source": [
    "allocation_mode=AllocationMode.from_str(\"sglang:d1p1t1+d1p1t1\")\n",
    "parallel_strategy = allocation_mode.train\n",
    "\n",
    "# initialize inference engine\n",
    "rollout = RemoteSGLangEngine(config.rollout)\n",
    "rollout.initialize(train_data_parallel_size=parallel_strategy.dp_size)\n",
    "workflow = GroupedReflectionWorkflow(\n",
    "    gconfig=GenerationHyperparameters(n_samples=3, max_new_tokens=512),\n",
    "    max_turns=5,\n",
    "    turn_discount=0.9,\n",
    "    verbose=False,\n",
    ")\n",
    "\n",
    "actor = FSDPPPOActor(config=config.actor)\n",
    "actor.create_process_group(parallel_strategy=parallel_strategy)\n",
    "actor.initialize(None, ft_spec)\n",
    "\n",
    "rollout = RemoteSGLangEngine(config.rollout)\n",
    "rollout.initialize()\n",
    "\n",
    "weight_update_meta = WeightUpdateMeta.from_fsdp_xccl(\n",
    "    allocation_mode\n",
    ")\n",
    "actor.connect_engine(rollout, weight_update_meta)\n",
    "\n",
    "warmup_steps = 1\n",
    "times = []\n",
    "for global_step in range(5):\n",
    "    if global_step >= warmup_steps:\n",
    "        tik = time.perf_counter()\n",
    "    batch = actor.rollout_batch(next(data_generator), \n",
    "                    granularity=actor.config.group_size,\n",
    "                    workflow=workflow,\n",
    "                    should_accept_fn=lambda sample: True,)\n",
    "    \n",
    "    logp = actor.compute_logp(batch)\n",
    "    batch[\"prox_logp\"] = logp\n",
    "\n",
    "    actor.compute_advantages(batch)\n",
    "\n",
    "    actor.ppo_update(batch)\n",
    "    actor.step_lr_scheduler()\n",
    "\n",
    "    rollout.pause()\n",
    "    actor.update_weights(weight_update_meta)\n",
    "    rollout.resume()\n",
    "    \n",
    "    actor.set_version(global_step + 1)\n",
    "    rollout.set_version(global_step + 1)\n",
    "    \n",
    "    if global_step >= warmup_steps:\n",
    "        times.append(time.perf_counter() - tik)\n",
    "print(times)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36",
   "metadata": {},
   "source": [
    "### Asynchronous Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize inference engine\n",
    "rollout = RemoteSGLangEngine(config.rollout)\n",
    "rollout.initialize(train_data_parallel_size=parallel_strategy.dp_size)\n",
    "workflow = GroupedReflectionWorkflow(\n",
    "    gconfig=GenerationHyperparameters(n_samples=3, max_new_tokens=512),\n",
    "    max_turns=5,\n",
    "    turn_discount=0.9,\n",
    "    verbose=False,\n",
    ")\n",
    "\n",
    "actor = FSDPPPOActor(config=config.actor)\n",
    "actor.create_process_group(parallel_strategy=parallel_strategy)\n",
    "actor.initialize(None, ft_spec)\n",
    "\n",
    "rollout = RemoteSGLangEngine(config.rollout)\n",
    "rollout.initialize()\n",
    "\n",
    "weight_update_meta = WeightUpdateMeta.from_fsdp_xccl(\n",
    "    allocation_mode\n",
    ")\n",
    "weight_update_meta.nccl_group_name = \"group2\"\n",
    "\n",
    "actor.connect_engine(rollout, weight_update_meta)\n",
    "\n",
    "warmup_steps = 1\n",
    "times = []\n",
    "for global_step in range(5):\n",
    "    if global_step >= warmup_steps:\n",
    "        tik = time.perf_counter()\n",
    "    batch = actor.prepare_batch(dataloader, \n",
    "                    granularity=actor.config.group_size,\n",
    "                    workflow=workflow,\n",
    "                    should_accept_fn=lambda sample: True,)\n",
    "    \n",
    "    logp = actor.compute_logp(batch)\n",
    "    batch[\"prox_logp\"] = logp\n",
    "\n",
    "    actor.compute_advantages(batch)\n",
    "\n",
    "    actor.ppo_update(batch)\n",
    "    actor.step_lr_scheduler()\n",
    "\n",
    "    rollout.pause()\n",
    "    actor.update_weights(weight_update_meta)\n",
    "    rollout.resume()\n",
    "    \n",
    "    actor.set_version(global_step + 1)\n",
    "    rollout.set_version(global_step + 1)\n",
    "    \n",
    "    if global_step >= warmup_steps:\n",
    "        times.append(time.perf_counter() - tik)\n",
    "print(times)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38",
   "metadata": {},
   "outputs": [],
   "source": [
    "import signal as signal_module\n",
    "\n",
    "import psutil\n",
    "\n",
    "\n",
    "def terminate_process_and_children(pid: int, signal=None):\n",
    "    if signal is None:\n",
    "        signal = signal_module.SIGKILL\n",
    "    if isinstance(signal, str):\n",
    "        signal = getattr(signal_module, signal)\n",
    "    try:\n",
    "        parent = psutil.Process(pid)\n",
    "        children = parent.children(recursive=True)\n",
    "        for child in children:\n",
    "            terminate_process_and_children(child.pid)\n",
    "        parent.send_signal(signal)\n",
    "    except psutil.NoSuchProcess:\n",
    "        pass\n",
    "\n",
    "\n",
    "terminate_process_and_children(sglang_process.pid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39",
   "metadata": {},
   "outputs": [],
   "source": [
    "rollout.destroy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40",
   "metadata": {},
   "outputs": [],
   "source": [
    "actor.destroy()"
   ]
  },
  {
   "attachments": {
    "6c881787-987e-473d-bc29-673dd1e0f2cc.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "41",
   "metadata": {},
   "source": [
    "![e69a9fbdc9c2fd12cdd85dbcc7d55093.png](attachment:6c881787-987e-473d-bc29-673dd1e0f2cc.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
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